title: Learning to Reason With Adaptive Computation

abstract:
  Multi-hop inference is necessary for machine learning systems to successfully
solve tasks such as Recognising Textual Entailment and Machine Reading. In this
work, we demonstrate the effectiveness of adaptive computation for learning the
number of inference steps required for examples of different complexity and
that learning the correct number of inference steps is difficult. We introduce
the first model involving Adaptive Computation Time which provides a small
performance benefit on top of a similar model without an adaptive component as
well as enabling considerable insight into the reasoning process of the model.


title:
Engineering One-Dimensional Quantum Stripes from Superlattices of
  Two-Dimensional Layered Materials

abstract:
  One-dimensional (1D) quantum systems, which are predicted to exhibit novel
states of matter in theory, have been elusive in experiment. Here we report a
superlattice method of creating artificial 1D quantum stripes, which offers
dimensional tunability from two- to one-dimensions. As a model system, we have
fabricated 1D iridium (Ir) stripes using a-axis oriented superlattices of a
relativistic Mott insulator Sr2IrO4 and a wide bandgap insulator LaSrGaO4, both
of which are crystals with layered structure. In addition to the successful
formation of 1D Ir-stripe structure, we have observed 1D quantum-confined
electronic states from optical spectroscopy and resonant inelastic x-ray
scattering. Since this 1D superlattice approach can be applied to a wide range
of layered materials, it opens a new era of 1D science.

categories: cond-mat.mtrl-sci cond-mat.other cond-mat.str-el cond-mat.supr-con


title: ALPINE: Anytime Mining with Definite Guarantees

abstract:
  ALPINE is to our knowledge the first anytime algorithm to mine frequent
itemsets and closed frequent itemsets. It guarantees that all itemsets with
support exceeding the current checkpoint's support have been found before it
proceeds further. Thus, it is very attractive for extremely long mining tasks
with very high dimensional data (for example in genetics) because it can offer
intermediate meaningful and complete results. This ANYTIME feature is the most
important contribution of ALPINE, which is also fast but not necessarily the
fastest algorithm around. Another critical advantage of ALPINE is that it does
not require the apriori decided minimum support value.


title:
A Theoretical Analysis of Noisy Sparse Subspace Clustering on
  Dimensionality-Reduced Data

abstract:
  Subspace clustering is the problem of partitioning unlabeled data points into
a number of clusters so that data points within one cluster lie approximately
on a low-dimensional linear subspace. In many practical scenarios, the
dimensionality of data points to be clustered are compressed due to constraints
of measurement, computation or privacy. In this paper, we study the theoretical
properties of a popular subspace clustering algorithm named sparse subspace
clustering (SSC) and establish formal success conditions of SSC on
dimensionality-reduced data. Our analysis applies to the most general fully
deterministic model where both underlying subspaces and data points within each
subspace are deterministically positioned, and also a wide range of
dimensionality reduction techniques (e.g., Gaussian random projection, uniform
subsampling, sketching) that fall into a subspace embedding framework (Meng &
Mahoney, 2013; Avron et al., 2014). Finally, we apply our analysis to a
differentially private SSC algorithm and established both privacy and utility
guarantees of the proposed method.


title: UTD-CRSS Systems for 2016 NIST Speaker Recognition Evaluation

abstract:
  This document briefly describes the systems submitted by the Center for
Robust Speech Systems (CRSS) from The University of Texas at Dallas (UTD) to
the 2016 National Institute of Standards and Technology (NIST) Speaker
Recognition Evaluation (SRE). We developed several UBM and DNN i-Vector based
speaker recognition systems with different data sets and feature
representations. Given that the emphasis of the NIST SRE 2016 is on language
mismatch between training and enrollment/test data, so-called domain mismatch,
in our system development we focused on: (1) using unlabeled in-domain data for
centralizing data to alleviate the domain mismatch problem, (2) finding the
best data set for training LDA/PLDA, (3) using newly proposed dimension
reduction technique incorporating unlabeled in-domain data before PLDA
training, (4) unsupervised speaker clustering of unlabeled data and using them
alone or with previous SREs for PLDA training, (5) score calibration using only
unlabeled data and combination of unlabeled and development (Dev) data as
separate experiments.


title:
The first moment of central values of symmetric square $L$-functions in
  the weight aspect

abstract:
  In this note we investigate the behavior at the central point of the
symmetric square $L$-functions, the most frequently used $\rm{GL}(3)$
$L$-functions. We establish an asymptotic formula with arbitrary power saving
for the first moment of $L(\frac{1}{2},{\rm{sym}}^2f)$ for $f\in\mathcal{H}_k$
as even $k\rightarrow\infty$, where $\mathcal{H}_k$ is an orthogonal basis of
weight-$k$ Hecke eigencuspforms for $SL(2,\mathbb{Z})$. The approach taken in
this note allows us to extract two secondary main terms from the error term
$O(k^{-\frac{1}{2}})$ in previous studies. More interestingly, our result
exhibits a connection between the symmetric square $L$-functions and quadratic
fields, which is the main theme of Zagier's work "Modular forms whose
coefficients involve zeta-functions of quadratic fields" in 1977. Specifically,
the secondary main terms in our asymptotic formula involve central values of
Dirichlet $L$-functions of characters $\chi_{-4}$ and $\chi_{-3}$ and depend on
the values of $k\,({\rm{mod}}\ 4)$ and $k\,({\rm{mod}}\ 6)$, respectively.


title:
Synchrotron radiation and absence of linear polarization in the
  colliding wind binary WR 146

abstract:
  Several massive early-type binaries exhibit non-thermal emission which has
been attributed to synchrotron radiation from particles accelerated by
diffusive shock acceleration (DSA) in the wind-collision region (WCR). If the
magnetic field in the strong shocks is ordered, its component parallel to the
shock front should be enhanced, and the resultant synchrotron radiation would
be polarized. However, such polarization has never been measured. We performed
spatially-unresolved radio continuum observations of WR 146, a well known a
WC6+O8 system, at 5 cm and 20 cm with the Karl G. Jansky Very Large Array. No
linearly polarized radio emission was detected. The data constrain the
fractional linear polarization to less than 0.6% between 1 to 8 GHz. This is
compatible with a high level of turbulence and a dominant random component in
the magnetic field. In this case the relativistic particles could be produced
by turbulent magnetic reconnection (MR). In order for this scenario to satisfy
the required non-thermal energy budget, we find through numerical modeling that
the strength of the magnetic field in the WCR must be as high as ~150 mG.
However, if the magnetic field is ordered and DSA is ongoing, then a
combination of internal and external Faraday rotation could equally account for
the depolarization of the emission. It is not clear whether it is possible to
develop the high level of turbulence and strong magnetic fields required for
efficient MR in a long-period binary such as WR 146. This scenario might also
have trouble explaining the low-frequency cutoff in the spectrum. We therefore
favor a scenario where particles are accelerated through DSA and the
depolarization is produced by mechanisms other than a large ratio between
random to regular magnetic fields.


title: After the Fall: Late-Time Spectroscopy of Type IIP Supernovae

abstract:
  Herein we analyse late-time (post-plateau; 103 < t < 1229 d) optical spectra
of low-redshift (z < 0.016), hydrogen-rich Type IIP supernovae (SNe IIP). Our
newly constructed sample contains 91 nebular spectra of 38 SNe IIP, which is
the largest dataset of its kind ever analysed in one study, and many of the
objects have complementary photometric data. We determined the peak and total
luminosity, velocity of the peak, HWHM intensity, and profile shape for many
emission lines. Temporal evolution of these values and various flux ratios are
studied. We also investigate the correlations between these measurements and
photometric observables, such as the peak and plateau absolute magnitudes and
the late-time light curve decline rates in various optical bands. The strongest
and most robust result we find is that the luminosities of all spectral
features (except those of helium) tend to be higher in objects with steeper
late-time V-band decline rates. A steep late-time V-band slope likely arises
from less efficient trapping of gamma-rays and positrons, which could be caused
by multidimensional effects such as clumping of the ejecta or asphericity of
the explosion itself. Furthermore, if gamma-rays and positrons can escape more
easily, then so can photons via the observed emission lines, leading to more
luminous spectral features. It is also shown that SNe IIP with larger
progenitor stars have ejecta with a more physically extended oxygen layer that
is well-mixed with the hydrogen layer. In addition, we find a subset of objects
with evidence for asymmetric Ni-56 ejection, likely bipolar in shape. We also
compare our observations to theoretical late-time spectral models of SNe IIP
from two separate groups and find moderate-to-good agreement with both sets of
models. Our SNe IIP spectra are consistent with models of 12-15 M_Sun
progenitor stars having relatively low metallicity (Z $\le$ 0.01).


title:
Deep Reactive Ion Etched Anti-Reflection Coatings for Sub-millimeter
  Silicon Optics

abstract:
  Refractive optical elements are widely used in millimeter and sub-millimeter
astronomical telescopes. High resistivity silicon is an excellent material for
dielectric lenses given its low loss-tangent, high thermal conductivity and
high index of refraction. The high index of refraction of silicon causes a
large Fresnel reflectance at the vacuum-silicon interface (up to 30%), which
can be reduced with an anti-reflection (AR) coating. In this work we report
techniques for efficiently AR coating silicon at sub-millimeter wavelengths
using Deep Reactive Ion Etching (DRIE) and bonding the coated silicon to
another silicon optic. Silicon wafers of 100 mm diameter (1 mm thick) were
coated and bonded using the Silicon Direct Bonding technique at high
temperature (1100 C). No glue is used in this process. Optical tests using a
Fourier Transform Spectrometer (FTS) show sub-percent reflections for a
single-layer DRIE AR coating designed for use at 320 microns on a single wafer.
Cryogenic (10 K) measurements of a bonded pair of AR-coated wafers also reached
sub-percent reflections. A prototype two-layer DRIE AR coating to reduce
reflections and increase bandwidth is presented and plans for extending this
approach are discussed.


title:
The coherent photon scattering background in sub-GeV/$c^2$ direct dark
  matter searches

abstract:
  Proposed dark matter detectors with eV-scale sensitivities will detect a
large background of atomic (nuclear) recoils from coherent photon scattering.
This background climbs steeply below $\sim10$~eVnr, far exceeding the declining
rate of low-energy Compton recoils. The upcoming generation of dark matter
detectors will not be limited by this background, but further development of
eV-scale and sub-eV detectors will require the use of low-$Z$ target materials,
such as helium, to avoid a large rate of coherent photon scattering, or highly
efficient methods to reject photons when they scatter.


title: Variational Carleson embeddings into the upper 3-space

abstract:
  In this paper we formulate embedding maps into time-frequency space related
to the Carleson operator and its variational counterpart. We prove bounds for
these embedding maps by iterating the outer measure theory of [DT15].
Introducing iterated outer $L^p$ spaces is a main novelty of this paper.
  [DT15] Yen Do and Christoph Thiele. "$L^p$ theory for outer measures and two
themes of Lennart Carleson united". In: Bulletin of the American Mathematical
Society 52.2 (2015), pp. 249-296.


title: On transfer operators on the circle with trigonometric weights

abstract:
  We study spectral properties of the transfer operators $L$ defined on the
circle $\mathbb T=\mathbb R/\mathbb Z$ by $$(Lu)(t)=\frac{1}{d}\sum_{i=0}^{d-1}
f\left(\frac{t+i}{d}\right)u\left(\frac{t+i}{d}\right),\ t\in\mathbb T$$ where
$u$ is a function on $\mathbb T$. We focus in particular on the cases
$f(t)=|\cos(\pi t)|^q$ and $f(t)=|\sin(\pi t)|^q$, which are closely related to
some classical Fourier-analytic questions. We also obtain some explicit
computations, particularly in the case $d=2$. Our study extends work of
Strichartz \cite{Strichartz1990} and Fan and Lau \cite{FanLau1998}.


title:
Spheroidal harmonic expansions for the solution of Laplace's equation
  for a point source near a sphere

abstract:
  We propose a powerful approach to solve Laplace's equation for point sources
near a spherical object. The central new idea is to use prolate spheroidal
solid harmonics, which are separable solutions of Laplace's equation in
spheroidal coordinates, instead of the more natural spherical solid harmonics.
We motivate this choice and show that the resulting series expansions converge
much faster. This improvement is discussed in terms of the singularity of the
solution and its analytic continuation. The benefits of this approach are
illustrated for a specific example: the calculation of modified decay rates of
light emitters close to nanostructures in the long-wavelength approximation. We
expect the general approach to be applicable with similar benefits to a variety
of other contexts, from other geometries to other equations of mathematical
physics.


title: Orthogonal polynomials on Cantor sets of zero Lebesgue measure

abstract:
  In this survey article, we review some results and conjectures related to
orthogonal polynomials on Cantor sets. The main purpose of this paper is to
emphasize the role of equilibrium measures in order to have a general theory of
sufficiently good measures (measures that behave similarly to measures which
are in the Szeg\H{o} class and the isospectral torus in the finite gap case)
supported on totally disconnected subsets of $\mathbb{R}$. We present some open
problems a number of which can be studied numerically.


title: Reissner Nordstrom Metric in Unimodular Theory of Gravity

abstract:
  We study the modified Reissner Nordstrom metric in the unimodular gravity. So
far the spherical symmetric Einstein field equation in unimodular gravity has
been studied in the absence of any source. We consider static electric and
magnetic charge as source. We solve for Maxwell equations in unimodular
gravitational background. We show that in unimodular gravity the
electromagnetic field strength tensor is modified. We also show that the
solution in unimodular gravity differs from the usual R-N metric in Einstein
gravity with some corrections. We further study the thermodynamical properties
of the R-N black-hole solution in this theory.


title: A New Class of Private Chi-Square Tests

abstract:
  In this paper, we develop new test statistics for private hypothesis testing.
These statistics are designed specifically so that their asymptotic
distributions, after accounting for noise added for privacy concerns, match the
asymptotics of the classical (non-private) chi-square tests for testing if the
multinomial data parameters lie in lower dimensional manifolds (examples
include goodness of fit and independence testing). Empirically, these new test
statistics outperform prior work, which focused on noisy versions of existing
statistics.


title:
The Mass-Discrepancy Acceleration Relation: a Natural Outcome of Galaxy
  Formation in Cold Dark Matter halos

abstract:
  We analyze the total and baryonic acceleration profiles of a set of
well-resolved galaxies identified in the EAGLE suite of hydrodynamic
simulations. Our runs start from the same initial conditions but adopt
different prescriptions for unresolved stellar and AGN feedback, resulting in
diverse populations of galaxies by the present day. Some of them reproduce
observed galaxy scaling relations, while others do not. However, regardless of
the feedback implementation, all of our galaxies follow closely a simple
relationship between the total and baryonic acceleration profiles, consistent
with recent observations of rotationally supported galaxies. The relation has
small scatter: different feedback implementations -- which produce different
galaxy populations -- mainly shift galaxies along the relation, rather than
perpendicular to it. Furthermore, galaxies exhibit a characteristic
acceleration, $g_{\dagger}$, above which baryons dominate the mass budget, as
observed. These observations, consistent with simple modified Newtonian
dynamics, can be accommodated within the standard cold dark matter paradigm.


title:
A robust quantitative local central limit theorem with applications to
  enumerative combinatorics and random combinatorial structures

abstract:
  A useful heuristic in the understanding of large random combinatorial
structures is the Arratia-Tavare principle, which describes an approximation to
the joint distribution of component-sizes using independent random variables.
The principle outlines conditions under which the total variation distance
between the true joint distribution and the approximation should be small, and
was successfully exploited by Pittel in the cases of integer partitions and set
partitions. We provide sufficient conditions for this principle to be true in a
general context, valid for certain discrete probability distributions which are
$\textit{perturbed log-concave}$, via a quantitative local central limit
theorem. We then use it to generalize some classical asymptotic statistics in
combinatorial theory, as well as assert some new ones.


title: Heisenberg quasiregular ellipticity

abstract:
  Following the Euclidean results of Varopoulos and Pankka--Rajala, we provide
a necessary topological condition for a sub-Riemannian 3-manifold $M$ to admit
a nonconstant quasiregular mapping from the sub-Riemannian Heisenberg group
$\mathbb{H}$. As an application, we show that a link complement $S^3\backslash
L$ has a sub-Riemannian metric admitting such a mapping only if $L$ is empty,
the unknot or Hopf link. In the converse direction, if $L$ is empty, a specific
unknot or Hopf link, we construct a quasiregular mapping from $\mathbb{H}$ to
$S^3\backslash L$.
  The main result is obtained by translating a growth condition on $\pi_1(M)$
into the existence of a supersolution to the $4$-harmonic equation, and relies
on recent advances in the study of analysis and potential theory on metric
spaces.


title:
Probing Intrinsic Material Conductivity in Two-Terminal Devices: A
  Resistance-Difference Method

abstract:
  It is generally impossible to separately measure the resistance of the
functional component (i.e., the intrinsic device materials) and the parasitic
component (i.e., terminals, interfaces and serial loads) in a two-terminal
device. Yet such knowledge is important for understanding device physics and
designing device systems. Here, we consider a case where an electric current,
temperature, or magnetic field causes a small but identical relative
conductivity change of the device materials. We find an exact solution to this
relative change by a simple resistance-data analysis of similarly configured
two-terminal devices. The solution is obtainable even if the change is quite
small, say, less than 0.1%. In special cases of small relative changes in
parasitic resistance, the absolute parasitic resistance is also obtainable. Our
method is especially useful for studying the switching and transport
characteristics of the emergent non-volatile resistance memory.


title:
Predicting Counterfactuals from Large Historical Data and Small
  Randomized Trials

abstract:
  When a new treatment is considered for use, whether a pharmaceutical drug or
a search engine ranking algorithm, a typical question that arises is, will its
performance exceed that of the current treatment? The conventional way to
answer this counterfactual question is to estimate the effect of the new
treatment in comparison to that of the conventional treatment by running a
controlled, randomized experiment. While this approach theoretically ensures an
unbiased estimator, it suffers from several drawbacks, including the difficulty
in finding representative experimental populations as well as the cost of
running such trials. Moreover, such trials neglect the huge quantities of
available control-condition data which are often completely ignored.
  In this paper we propose a discriminative framework for estimating the
performance of a new treatment given a large dataset of the control condition
and data from a small (and possibly unrepresentative) randomized trial
comparing new and old treatments. Our objective, which requires minimal
assumptions on the treatments, models the relation between the outcomes of the
different conditions. This allows us to not only estimate mean effects but also
to generate individual predictions for examples outside the randomized sample.
  We demonstrate the utility of our approach through experiments in three
areas: Search engine operation, treatments to diabetes patients, and market
value estimation for houses. Our results demonstrate that our approach can
reduce the number and size of the currently performed randomized controlled
experiments, thus saving significant time, money and effort on the part of
practitioners.


title:
An explicit family of cubic number fields with large $2$-rank of the
  class group

abstract:
  We show how to construct infinite families of explicitly determined cubic
number fields whose class group has a subgroup isomorphic to $(\mathbb{Z}/2)^8$
using degree $1$ del Pezzo surfaces. We illustrate the method and provide an
example of such a family.


title: Saturn Variable Thermosphere

abstract:
  Our knowledge of Saturns neutral thermosphere is far superior to that of the
other giant planets due to Cassini Ultraviolet Imaging Spectrograph (UVIS)
observations of 15 solar occultations and 26 stellar occultations analyzed to
date. These measurements yield H2 as the dominant species with an upper limit
on the H mole fraction of 5 %. Inferred temperatures near the lower boundary
are ~ 150 K, rising to an asymptotic value of ~ 400K at equatorial latitudes
and increasing with latitude to polar values in the range of 550-600 K. The
latter is consistent with a total estimated auroral power input of ~ 10TW
generating Joule and energetic particle heating of ~ 5-6TW that is more than an
order of magnitude greater than solar EUV/FUV heating. This auroral heating
would be sufficient to solve the energy crisis of Saturns thermospheric
heating, if it can be efficiently redistributed to low latitudes. The inferred
structure of the thermosphere yields poleward directed pressure gradients on
equipotential surfaces consistent with auroral heating and poleward increasing
temperatures. A gradient wind balance aloft with these pressure gradients
implies westward, retrograde winds ~ 500 m/s or Mach number ~ 0.3 at
mid-latitudes. The occultations reveal an expansion of the thermosphere peaking
at or slightly after equinox, anti-correlated with solar activity, and
apparently driven by lower thermospheric heating of unknown cause. The He mole
fraction remains unconstrained as no Cassini UVIS He 58.4 nm airglow
measurements have been published.


title: A Framework for Network AB Testing

abstract:
  A/B testing, also known as controlled experiment, bucket testing or splitting
testing, has been widely used for evaluating a new feature, service or product
in the data-driven decision processes of online websites. The goal of A/B
testing is to estimate or test the difference between the treatment effects of
the old and new variations. It is a well-studied two-sample comparison problem
if each user's response is influenced by her treatment only. However, in many
applications of A/B testing, especially those in HIVE of Yahoo and other social
networks of Microsoft, Facebook, LinkedIn, Twitter and Google, users in the
social networks influence their friends via underlying social interactions, and
the conventional A/B testing methods fail to work. This paper considers the
network A/B testing problem and provide a general framework consisting of five
steps: data sampling, probabilistic model, parameter inference, computing
average treatment effect and hypothesis test. The framework performs well for
network A/B testing in simulation studies.


title: Sparser Sparse Roadmaps

abstract:
  We present methods for offline generation of sparse roadmap spanners that
result in graphs 79% smaller than existing approaches while returning solutions
of equivalent path quality. Our method uses a hybrid approach to sampling that
combines traditional graph discretization with random sampling. We present
techniques that optimize the graph for the L1-norm metric function commonly
used in joint-based robotic planning, purposefully choosing a $t$-stretch
factor based on the geometry of the space, and removing redundant edges that do
not contribute to the graph quality. A high-quality pre-processed sparse
roadmap is then available for re-use across many different planning scenarios
using standard repair and re-plan methods. Pre-computing the roadmap offline
results in more deterministic solutions, reduces the memory requirements by
affording complex rejection criteria, and increases the speed of planning in
high-dimensional spaces allowing more complex problems to be solved such as
multi-modal task planning. Our method is validated through simulated benchmarks
against the SPARS2 algorithm. The source code is freely available online as an
open source extension to OMPL.


title: Wirelessly Powered Communication Networks with Short Packets

abstract:
  Wirelessly powered communications will entail short packets due to naturally
small payloads, low-latency requirements and/or insufficient energy resources
to support longer transmissions. In this paper, a wirelessly powered
communication system is investigated where an energy harvesting transmitter,
charged by one or more power beacons via wireless energy transfer, attempts to
communicate with a receiver over a noisy channel. Under a save-then-transmit
protocol, the system performance is characterized using metrics such as the
energy supply probability at the transmitter, and the achievable rate at the
receiver for the case of short packets. Leveraging the framework of
finite-length information theory, tractable analytical expressions are derived
for the considered metrics in terms of system parameters such as the harvest
blocklength, the transmit blocklength, the harvested power and the transmit
power. The analysis provides several useful design guidelines. Though using a
small transmit power or a small transmit blocklength helps avoid energy
outages, the consequently smaller signal-to-noise ratio or the fewer coding
opportunities may cause an information outage. Scaling laws are derived to
capture this inherent trade-off between the harvest and transmit blocklengths.
Moreover, the asymptotically optimal transmit power is derived in closed-form.
Numerical results reveal that power control is essential for improving the
achievable rate of the system in the finite blocklength regime. The
asymptotically optimal transmit power yields nearly optimal performance in the
finite blocklength regime.


title:
Topology-Scaling Identification of Layered Solids and Stable Exfoliated
  2D Materials

abstract:
  The Materials Project crystal structure database has been searched for
materials possessing layered motifs in their crystal structures using a
topology-scaling algorithm. The algorithm identifies and measures the sizes of
bonded atomic clusters in a structure's unit cell, and determines their scaling
with cell size. The search yielded 826 stable layered materials, which are
considered as candidates for the formation of two-dimensional monolayers via
exfoliation. Density-functional theory calculates the exfoliation energy of
each material and 681 monolayers are found to exhibit exfoliation energies
below those of certain already-extant two-dimensional materials, indicating the
possibility of exfoliating them from bulk phases. The crystal structures of
these two-dimensional materials provide templates for future theoretical
searches of stable two-dimensional materials. The optimized structures and
other data for all 826 monolayers are provided at https://materialsweb.org .


title:
The X-ray luminosity-temperature relation of a complete sample of
  low-mass galaxy clusters

abstract:
  We present \Chandra\ observations of 23 galaxy groups and low-mass galaxy
clusters at $0.03<z<0.15$ with a median temperature of ~2keV. The sample is a
statistically complete flux-limited subset of the 400 deg$^2$ survey. We
investigated the scaling relation between X-ray luminosity ($L$) and
temperature ($T$), taking selection biases fully into account. The logarithmic
slope of the bolometric \LT\ relation was found to be $3.29\pm0.33$, consistent
with values typically found for samples of more massive clusters. In
combination with other recent studies of the \LT\ relation we show that there
is no evidence for the slope, normalisation, or scatter of the \LT\ relation of
galaxy groups being different than that of massive clusters. The exception to
this is that in the special case of the most relaxed systems, the slope of the
core-excised \LT\ relation appears to steepen from the self-similar value found
for massive clusters to a steeper slope for the lower mass sample studied here.
Thanks to our rigorous treatment of selection biases, these measurements
provide a robust reference against which to compare predictions of models of
the impact of feedback on the X-ray properties of galaxy groups.


title: Surprisal-Driven Zoneout

abstract:
  We propose a novel method of regularization for recurrent neural networks
called suprisal-driven zoneout. In this method, states zoneout (maintain their
previous value rather than updating), when the suprisal (discrepancy between
the last state's prediction and target) is small. Thus regularization is
adaptive and input-driven on a per-neuron basis. We demonstrate the
effectiveness of this idea by achieving state-of-the-art bits per character of
1.31 on the Hutter Prize Wikipedia dataset, significantly reducing the gap to
the best known highly-engineered compression methods.


title: Analysis of mesoscale forecasts using ensemble methods

abstract:
  Mesoscale forecasts are now routinely performed as elements of operational
forecasts and their outputs do appear convincing. However, despite their
realistic appearance at times the comparison to observations is less favorable.
At the grid scale these forecasts often do not compare well with observations.
This is partly due to the chaotic system underlying the weather. Another key
problem is that it is impossible to evaluate the risk of making decisions based
on these forecasts because they do not provide a measure of confidence.
Ensembles provide this information in the ensemble spread and quartiles.
However, running global ensembles at the meso or sub mesoscale involves
substantial computational resources. National centers do run such ensembles,
but the subject of this publication is a method which requires significantly
less computation. The ensemble enhanced mesoscale system presented here aims
not at the creation of an improved mesoscale forecast model. Also it is not to
create an improved ensemble system. Here an ensemble is created from one
mesoscale forecast with the aim of interrogating the probabilities of the
forecast. The diagnostics developed in this publication is the generation of
the confidence intervals via cumulative probability density functions (pdf),
detection of extrema and selective ensembles. The subject of this publication
is the analysis of those diagnostics, their dependence on the domain size of
the ensemble and the number of ensemble members. The analysis strategies
introduced are termed: subgrid ensemble enhanced mesoscale forecast, extreme
value analysis of the ensemble pdf and observation constrained ensemble
forecast.


title: A Bayesian Ensemble for Unsupervised Anomaly Detection

abstract:
  Methods for unsupervised anomaly detection suffer from the fact that the data
is unlabeled, making it difficult to assess the optimality of detection
algorithms. Ensemble learning has shown exceptional results in classification
and clustering problems, but has not seen as much research in the context of
outlier detection. Existing methods focus on combining output scores of
individual detectors, but this leads to outputs that are not easily
interpretable. In this paper, we introduce a theoretical foundation for
combining individual detectors with Bayesian classifier combination. Not only
are posterior distributions easily interpreted as the probability distribution
of anomalies, but bias, variance, and individual error rates of detectors are
all easily obtained. Performance on real-world datasets shows high accuracy
across varied types of time series data.


title:
Why do magnetic nanoparticles form messy clumps? Taking into account the
  bridging or sticking of ligands in simulations

abstract:
  Experiments on magnetic nanoparticles in a viscous medium have shown that
agglomerates form that display complex shapes. However, most theoretical
results predict more simple, ordered shapes, such as single-particle width
chains. To account for this discrepancy we have created a theoretical model
that phenomenologically includes the bridging or "stickiness" between ligands
on nearby nanoparticles. This interaction is accounted for through a unitless
stickiness parameter c that can be varied between 0 (no bridging between
ligands) and 1 (irreversible bridging or sticking together on impact). An
analytic estimate for the value of c is provided based on a comparison between
the time for a particle to diffuse to an agglomerate compared to the time for
it to reorient into the local magnetic field direction. Numerical Langevin
simulations are performed using ferromagnetic, 50 nm and 25 nm diameter
magnetite nanoparticles with various ligand coating lengths in hexane in order
to support the analytic estimate. The simulations produce agglomerates that are
qualitatively and quantitatively similar to experimental results.


title:
Jupiter's Phase Variations from Cassini: a testbed for future
  direct-imaging missions

abstract:
  We present phase curves of Jupiter from 0-140 degrees as measured in multiple
optical bandpasses by Cassini/ISS during the Millennium flyby of Jupiter in
late 2000 to early 2001. Phase curves are of interest for studying the energy
balance of Jupiter and understanding the scattering behavior of Jupiter as an
exoplanet analog. We find that Jupiter is significantly darker at partial
phases than an idealized Lambertian planet by roughly 25% and is not well fit
by Jupiter-like exoplanet atmospheric models across all wavelengths. We provide
analytic fits to Jupiter's phase function in several Cassini/ISS imaging filter
bandpasses. In addition, these observations show that Jupiter's color is more
variable with phase angle than predicted by models. Therefore, the color of
even a near Jupiter-twin planet observed at a partial phase cannot be assumed
to be comparable to that of Jupiter at full phase. We discuss how WFIRST and
other future direct-imaging missions can enhance the study of cool giants.


title: Counting Zeros of Cosine Polynomials: On a Problem of Littlewood

abstract:
  We show that if $A$ is a finite set of non-negative integers then the number
of zeros of the function \[ f_A(\theta) = \sum_{a \in A} \cos(a\theta), \] in
$[0,2\pi]$, is at least $(\log \log \log |A|)^{1/2-\varepsilon}$. This gives
the first unconditional lower bound on a problem of Littlewood, solves a
conjecture of Borwein, Erd\'elyi, Ferguson and Lockhart and improves upon work
of Borwein and Erd\'elyi. We also prove a result that applies to more general
cosine polynomials with "few" distinct rational coefficients. One of the main
ingredients in the proof is perhaps of independent interest: we show that if
$f$ is an exponential polynomial with "few" distinct integer coefficients and
$f$ "correlates" with a low-degree exponential polynomial $P$, then $f$ has a
very particular structure.


title:
Degenerations of the generic square matrix. Polar map and determinantal
  structure

abstract:
  One studies certain degenerations of the generic square matrix over a field
$k$ along with its main related structures, such as the determinant of the
matrix, the ideal generated by its partial derivatives, the polar map defined
by these derivatives, the Hessian matrix and the ideal of the submaximal minors
of the matrix. The main tool comes from commutative algebra, with emphasis on
ideal theory and syzygy theory. The structure of the polar map is completely
identified and the main properties of the ideal of submaximal minors are
determined. Cases where the degenerated determinant has non-vanishing Hessian
determinant show that the former is a factor of the latter with the (Segre)
expected multiplicity, a result treated by Landsberg-Manivel-Ressayre by
geometric means. Another byproduct is an affirmative answer to a question of F.
Russo concerning the codimension in the polar image of the dual variety to a
hypersurface.


title: Molino's description and foliated homogeneity

abstract:
  The topological Molino's description of equicontinuous foliated spaces,
studied by the first author and Moreira Galicia, gives conditions to reduce
their study to the particular case where the holonomy pseudogroup can be
represented by a pseudogroup on some local group $G$ generated by some of its
local left translations (a $G$-foliated space). That description is sharpened
in this paper by introducing a foliated action of a compact topological group
on the resulting $G$-foliated space, like in the case of Riemannian foliations.
Moreover a $C^\infty$ version is also studied. The triviality of this compact
group characterizes compact minimal $G$-foliated spaces, which are also
characterized by their foliated homogeneity in the $C^\infty$ case. We also
give an example where the projection of the Molino's description is not a
principal bundle, and another example of positive topological codimension where
the foliated homogeneity cannot be checked by only comparing pairs of
leaves---in the case of zero topological codimension, weak solenoids with this
property were given by Fokkink and Oversteegen, and later by Dyer, Hurder and
Lukina.


title:
Combined Hypothesis Testing on Graphs with Applications to Gene Set
  Enrichment Analysis

abstract:
  Motivated by gene set enrichment analysis, we investigate the problem of
combined hypothesis testing on a graph. We introduce a general framework to
effectively use the structural information of the underlying graph when testing
multivariate means. A new testing procedure is proposed within this framework.
We show that the test is optimal in that it can consistently detect departure
from the collective null at a rate that no other test could improve, for almost
all graphs. We also provide general performance bounds for the proposed test
under any specific graph, and illustrate their utility through several common
types of graphs. Numerical experiments are presented to further demonstrate the
merits of our approach.


title:
Exploratory Analysis of High Dimensional Time Series with Applications
  to Multichannel Electroencephalograms

abstract:
  In this paper, we address the the major hurdle of high dimensionality in EEG
analysis by extracting the optimal lower dimensional representations. Using our
approach, connectivity between regions in a high-dimensional brain network is
characterized through the connectivity between region-specific factors. The
proposed approach is motivated by our observation that electroencephalograms
(EEGs) from channels within each region exhibit a high degree of
multicollinearity and synchrony. These observations suggest that it would be
sensible to extract summary factors for each region. We consider the general
approach for deriving summary factors which are solutions to the criterion of
squared error reconstruction. In this work, we focus on two special cases of
linear auto encoder and decoder. In the first approach, the factors are
characterized as instantaneous linear mixing of the observed high dimensional
time series. In the second approach, the factors signals are linear filtered
versions of the original signal which is more general than an instantaneous
mixing. This exploratory analysis is the starting point to the multi-scale
factor analysis model where the concatenated factors from all regions are
represented by vector auto-regressive model that captures the connectivity in
high dimensional signals. We performed evaluations on the two approaches via
simulations under different conditions. The simulation results provide insights
on the performance and application scope of the methods. We also performed
exploratory analysis of EEG recorded over several epochs during resting state.
Finally, we implemented these exploratory methods in a Matlab toolbox XHiDiTS
available from https://goo.gl/uXc8ei .


title: The Markov Memory for Generating Rare Events

abstract:
  We classify the rare events of structured, memoryful stochastic processes and
use this to analyze sequential and parallel generators for these events. Given
a stochastic process, we introduce a method to construct a new process whose
typical realizations are a given process' rare events. This leads to an
expression for the minimum memory required to generate rare events. We then
show that the recently discovered classical-quantum ambiguity of simplicity
also occurs when comparing the structure of process fluctuations.

categories: cond-mat.stat-mech cs.CC cs.IT math.IT nlin.CD


title: Co-Occuring Directions Sketching for Approximate Matrix Multiply

abstract:
  We introduce co-occurring directions sketching, a deterministic algorithm for
approximate matrix product (AMM), in the streaming model. We show that
co-occuring directions achieves a better error bound for AMM than other
randomized and deterministic approaches for AMM. Co-occurring directions gives
a $1 + \epsilon$ -approximation of the optimal low rank approximation of a
matrix product. Empirically our algorithm outperforms competing methods for
AMM, for a small sketch size. We validate empirically our theoretical findings
and algorithms


title:
Policy Design for Controlling Set-Point Temperature of ACs in Shared
  Spaces of Buildings

abstract:
  Air conditioning systems are responsible for the major percentage of energy
consumption in buildings. Shared spaces constitute considerable office space
area, in which most office employees perform their meetings and daily tasks,
and therefore the ACs in these areas have significant impact on the energy
usage of the entire office building. The cost of this energy consumption,
however, is not paid by the shared space users, and the AC's temperature
set-point is not determined based on the users' preferences. This latter factor
is compounded by the fact that different people may have different choices of
temperature set-points and sensitivities to change of temperature. Therefore,
it is a challenging task to design an office policy to decide on a particular
set-point based on such a diverse preference set. As a result, users are not
aware of the energy consumption in shared spaces, which may potentially
increase the energy wastage and related cost of office buildings. In this
context, this paper proposes an energy policy for an office shared space by
exploiting an established temperature control mechanism. In particular, we
choose meeting rooms in an office building as the test case and design a policy
according to which each user of the room can give a preference on the
temperature set-point and is paid for felt discomfort if the set-point is not
fixed according to the given preference. On the other hand, users who enjoy the
thermal comfort compensate the other users of the room. Thus, the policy
enables the users to be cognizant and responsible for the payment on the energy
consumption of the office space they are sharing, and at the same time ensures
that the users are satisfied either via thermal comfort or through incentives.
The policy is also shown to be beneficial for building management. Through
experiment based case studies, we show the effectiveness of the proposed
policy.


title:
Large Electronic Anisotropy and Enhanced Chemical Activity of Highly
  Rippled Phosphorene

abstract:
  We investigate the electronic structure and chemical activity of rippled
phosphorene induced by large compressive strains via first-principles
calculation. It is found that phosphorene is extraordinarily bendable, enabling
the accommodation of ripples with large curvatures. Such highly rippled
phosphorene shows a strong anisotropy in electronic properties. For ripples
along the armchair direction, the band gap changes from 0.84 to 0.51 eV for the
compressive strain up to -20% and further compression shows no significant
effect, for ripples along the zigzag direction, semiconductor to metal
transition occurs. Within the rippled phosphorene, the local electronic
properties, such as the modulated band gap and the alignments of frontier
orbitals, are found to be highly spatially dependent, which may be used for
modulating the injection and confinement of carriers for optical and
photovoltaic applications. The examination of the interaction of a physisorbed
NO molecule with the rippled phosphorene under different compressive strains
shows that the chemical activities of the phosphorene are significantly
enhanced at the top and bottom peaks of the ripples, indicated by the enhanced
adsorption and charge transfer between them. All these features can be ascribed
to the effect of curvatures, which modifies the orbital coupling between atoms
at the ripple peaks.


title: Pumped-up SU(1,1) interferometry

abstract:
  Although SU(1,1) interferometry achieves Heisenberg-limited sensitivities, it
suffers from one major drawback: only those particles outcoupled from the pump
mode contribute to the phase measurement. Since the number of particles
outcoupled to these `side modes' is typically small, this limits the
interferometer's absolute sensitivity. We propose an alternative `pumped-up'
approach where all the input particles participate in the phase measurement,
and show how this can be implemented in spinor Bose-Einstein condensates and
hybrid atom-light systems - both of which have experimentally realized SU(1,1)
interferometry. We demonstrate that pumped-up schemes are capable of surpassing
the shot-noise limit with respect to the total number of input particles and
are never worse than conventional SU(1,1) interferometry. Finally, we show that
pumped-up schemes continue to excel - both absolutely and in comparison to
conventional SU(1,1) interferometry - in the presence of particle losses, poor
particle-resolution detection, and noise on the relative phase difference
between the two side modes. Pumped-up SU(1,1) interferometry therefore pushes
the advantages of conventional SU(1,1) interferometry into the regime of high
absolute sensitivity, which is a necessary condition for useful
quantum-enhanced devices.


title: Operational Calculus for Differentiable Programming

abstract:
  In this work we present a theoretical model for differentiable programming.
We construct an algebraic language that encapsulates formal semantics of
differentiable programs by way of Operational Calculus. The algebraic nature of
Operational Calculus can alter the properties of the programs that are
expressed within the language and transform them into their solutions.
  In our model programs are elements of programming spaces and viewed as maps
from the virtual memory space to itself. Virtual memory space is an algebra of
programs, an algebraic data structure one can calculate with. We define the
operator of differentiation ($\partial$) on programming spaces and, using its
powers, implement the general shift operator and the operator of program
composition. We provide the formula for the expansion of a differentiable
program into an infinite tensor series in terms of the powers of $\partial$. We
express the operator of program composition in terms of the generalized shift
operator and $\partial$, which implements a differentiable composition in the
language. Such operators serve as abstractions over the tensor series algebra,
as main actors in our language.
  We demonstrate our models usefulness in differentiable programming by using
it to analyse iterators, deriving fractional iterations and their iterating
velocities, and explicitly solve the special case of ReduceSum.


title: Non-existence of boundary maps for some hierarchically hyperbolic spaces

abstract:
  We provide negative answers to questions posed by Durham, Hagen, and Sisto on
the existence of boundary maps for some hierarchically hyperbolic spaces,
namely maps from right-angled Artin groups to mapping class groups. We also
prove results on existence of boundary maps for free subgroups of mapping class
groups.


title:
Numerical simulations of Ising spin glasses with free boundary
  conditions: the role of droplet excitations and domain walls

abstract:
  The relative importance of the contributions of droplet excitations and
domain walls on the ordering of short-range Edwards-Anderson spin glasses in
three and four dimensions is studied. We compare the overlap distributions of
periodic and free boundary conditions using population annealing Monte Carlo.
For system sizes up to about 1000 spins, spin glasses show non-trivial spin
overlap distributions. Periodic boundary conditions can trap diffusive domain
walls which can contribute to small spin overlaps, and the other contribution
is the existence of low-energy droplet excitations within the system. We use
free boundary conditions to minimize domain-wall effects, and show that
low-energy droplet excitations are the major contribution to small overlaps in
numerical simulations. Free boundary conditions has stronger finite-size
effects, and is likely to have the same thermodynamic limit with periodic
boundary conditions.


title:
Supervised-Learning-Aided Communication Framework for MIMO Systems with
  Low-Resolution ADCs

abstract:
  This paper considers a multiple-input-multiple-output (MIMO) system with
low-resolution analog-to-digital converters (ADCs). In this system, we propose
a novel communication framework that is inspired by supervised learning. The
key idea of the proposed framework is to learn the non-linear input-output
system, formed by the concatenation of a wireless channel and a quantization
function used at the ADCs, for data detection. In this framework, a
conventional channel estimation process is replaced by a system learning
process, in which the conditional probability mass functions (PMFs) of the
nonlinear system are empirically learned by sending the repetitions of all
possible data signals as pilot signals. Then the subsequent data detection
process is performed based on the empirical conditional PMFs obtained during
the system learning. To reduce both the training overhead and the detection
complexity, we also develop a supervised-learning-aided
successive-interference-cancellation method. In this method, a data signal
vector is divided into two subvectors with reduced dimensions. Then these two
subvectors are successively detected based on the conditional PMFs that are
learned using artificial noise signals and an estimated channel. For the case
of one-bit ADCs, we derive an analytical expression for vector-error-rate of
the proposed framework under perfect channel knowledge at the receiver.
Simulations demonstrate the detection error reduction of the proposed framework
compared to conventional detection techniques that are based on channel
estimation.


title:
Dynamic portfolio optimization with liquidity cost and market impact: a
  simulation-and-regression approach

abstract:
  We present a simulation-and-regression method for solving dynamic portfolio
allocation problems in the presence of general transaction costs, liquidity
costs and market impacts. This method extends the classical least squares Monte
Carlo algorithm to incorporate switching costs, corresponding to transaction
costs and transient liquidity costs, as well as multiple endogenous state
variables, namely the portfolio value and the asset prices subject to permanent
market impacts. To do so, we improve the accuracy of the control randomization
approach in the case of discrete controls, and propose a global iteration
procedure to further improve the allocation estimates. We validate our
numerical method by solving a realistic cash-and-stock portfolio with a
power-law liquidity model. We quantify the certainty equivalent losses
associated with ignoring liquidity effects, and illustrate how our dynamic
allocation protects the investor's capital under illiquid market conditions.
Lastly, we analyze, under different liquidity conditions, the sensitivities of
certainty equivalent returns and optimal allocations with respect to trading
volume, stock price volatility, initial investment amount, risk-aversion level
and investment horizon.


title: The need for accurate redshifts in supernova cosmology

abstract:
  Recent papers have shown that a small systematic redshift shift ($\Delta
z\sim 10^{-5}$) in measurements of type Ia supernovae can cause a significant
bias ($\sim$1\%) in the recovery of cosmological parameters. Such a redshift
shift could be caused, for example, by a gravitational redshift due to the
density of our local environment. The sensitivity of supernova data to redshift
shifts means supernovae make excellent probes of inhomogeneities. We therefore
invert the analysis, and try to diagnose the nature of our local gravitational
environment by fitting for $\Delta z$ as an extra free parameter alongside the
usual cosmological parameters.


title:
Proceedings 14th International Workshop Quantitative Aspects of
  Programming Languages and Systems

abstract:
  This volume contains the post-proceedings of the 14th International Workshop
on Quantitative Aspects of Programming Languages and Systems (QAPL), held as a
satellite workshop of ETAPS 2016 in Eindhoven, The Netherlands, on 2-3 April
2016.


title: Embracing the Blessing of Dimensionality in Factor Models

abstract:
  Factor modeling is an essential tool for exploring intrinsic dependence
structures among high-dimensional random variables. Much progress has been made
for estimating the covariance matrix from a high-dimensional factor model.
However, the blessing of dimensionality has not yet been fully embraced in the
literature: much of the available data is often ignored in constructing
covariance matrix estimates. If our goal is to accurately estimate a covariance
matrix of a set of targeted variables, shall we employ additional data, which
are beyond the variables of interest, in the estimation? In this paper, we
provide sufficient conditions for an affirmative answer, and further quantify
its gain in terms of Fisher information and convergence rate. In fact, even an
oracle-like result (as if all the factors were known) can be achieved when a
sufficiently large number of variables is used. The idea of utilizing data as
much as possible brings computational challenges. A divide-and-conquer
algorithm is thus proposed to alleviate the computational burden, and also
shown not to sacrifice any statistical accuracy in comparison with a pooled
analysis. Simulation studies further confirm our advocacy for the use of full
data, and demonstrate the effectiveness of the above algorithm. Our proposal is
applied to a microarray data example that shows empirical benefits of using
more data.


title:
Singular SDEs with critical non-local and non-symmetric L\'evy type
  generator

abstract:
  In this work, by using Levi's parametrix method we first construct the
fundamental solution of the critical non-local operator perturbed by gradient.
Then, we use the obtained estimates to prove the existence and uniqueness of
strong solutions for stochastic differential equation driven by Markov process
with irregular coefficients, whose generator is a non-local and non-symmetric
L\'evy type operator.


title:
ATCA detections of massive molecular gas reservoirs in dusty, high-z
  radio galaxies

abstract:
  Observations using the 7 mm receiver system on the Australia Telescope
Compact Array have revealed large reservoirs of molecular gas in two
high-redshift radio galaxies: HATLAS J090426.9+015448 (z = 2.37) and HATLAS
J140930.4+003803 (z = 2.04). Optically the targets are very faint, and
spectroscopy classifies them as narrow-line radio galaxies. In addition to
harbouring an active galactic nucleus the targets share many characteristics of
sub-mm galaxies. Far-infrared data from Herschel-ATLAS suggest high levels of
dust (>10^9 M_solar) and a correspondingly large amount of obscured star
formation (~1000 M_solar / yr). The molecular gas is traced via the J = 1-0
transition of 12CO, its luminosity implying total H_2 masses of (1.7 +/- 0.3) x
10^11 and (9.5 +/- 2.4) x 10^10 (alpha_CO/0.8) M_solar in HATLAS
J090426.9+015448 and HATLAS J140930.4+003803 respectively. Both galaxies
exhibit molecular line emission over a broad (~1000 km/s) velocity range, and
feature double-peaked profiles. We interpret this as evidence of either a large
rotating disk or an on-going merger. Gas depletion timescales are ~100 Myr. The
1.4 GHz radio luminosities of our targets place them close to the break in the
luminosity function. As such they represent `typical' z > 2 radio sources,
responsible for the bulk of the energy emitted at radio wavelengths from
accretion-powered sources at high redshift, and yet they rank amongst the most
massive systems in terms of molecular gas and dust content. We also detect 115
GHz rest-frame continuum emission, indicating a very steep high-radio-frequency
spectrum, possibly classifying the targets as compact steep spectrum objects.


title:
Proceedings of the First International Workshop on Formal Methods for
  and on the Cloud

abstract:
  Cloud solutions are increasingly used for a plethora of purposes, including
solving memory-intensive and computation-intensive problems. Ensuring the
reliability, availability, scalability, and security of cloud solutions, as
networked distributed systems with properties such as dynamic reallocation of
resources, is a challenging problem that requires rigorous modeling, analysis,
and verification tools. Such tools can be devised using the techniques provided
by the formal methods community. On the other hand, many formal analysis and
verification tools are memory-intensive and computation-intensive solutions,
which can benefit from the cloud technology.
  The goal of the iFMCloud workshop is to identify and better understand
challenges of using formal and semi-formal methods for modeling and
verification of Cloud-based systems and computer and communication networks, as
well as challenges and opportunities in providing formal analysis and
verification as services on the Cloud. We aim to reach these goals by bringing
together researchers and practitioners from these, and other related fields.


title: A three-person deterministic graphical game without Nash equilibria

abstract:
  We give an example of a three-person deterministic graphical game that has no
Nash equilibrium in pure stationary strategies. The game has seven positions,
four outcomes (a unique cycle and three terminal positions), and its normal
form is of size 2 x 2 x 4 only. Thus, our example strengthens significantly the
one obtained in 2014 by Gurvich and Oudalov; the latter has four players, five
terminals, and a 2 x 4 x 6 x 8 normal form. Furthermore, our example is minimal
with respect to the number of players. Both examples are tight but not
Nash-solvable. Such examples were known since 1975, but they were not related
to deterministic graphical games. Moreover, due to the small size of our
example, we can strengthen it further by showing that it has no Nash
equilibrium not only in pure but also in independently mixed strategies, for
both Markovian and a priori evaluations.


title: New easy-plane $\mathbb{CP}^{N-1}$ fixed points

abstract:
  We study fixed points of the easy-plane $\mathbb{CP}^{N-1}$ field theory by
combining quantum Monte Carlo simulations of lattice models of easy-plane
SU($N$) superfluids with field theoretic renormalization group calculations, by
using ideas of deconfined criticality. From our simulations, we present
evidence that at small $N$ our lattice model has a first order phase transition
which progressively weakens as $N$ increases, eventually becoming continuous
for large values of $N$. Renormalization group calculations in $4-\epsilon$
dimensions provide an explanation of these results as arising due to the
existence of an $N_{ep}$ that separates the fate of the flows with easy-plane
anisotropy. When $N<N_{ep}$ the renormalization group flows to a discontinuity
fixed point and hence a first order transition arises. On the other hand, for
$N > N_{ep}$ the flows are to a new easy-plane $\mathbb{CP}^{N-1}$ fixed point
that describes the quantum criticality in the lattice model at large $N$. Our
lattice model at its critical point thus gives efficient numerical access to a
new strongly coupled gauge-matter field theory.


title:
Scalable Dynamic Topic Modeling with Clustered Latent Dirichlet
  Allocation (CLDA)

abstract:
  Topic modeling, a method for extracting the underlying themes from a
collection of documents, is an increasingly important component of the design
of intelligent systems enabling the sense-making of highly dynamic and diverse
streams of text data. Traditional methods such as Dynamic Topic Modeling (DTM)
do not lend themselves well to direct parallelization because of dependencies
from one time step to another. In this paper, we introduce and empirically
analyze Clustered Latent Dirichlet Allocation (CLDA), a method for extracting
dynamic latent topics from a collection of documents. Our approach is based on
data decomposition in which the data is partitioned into segments, followed by
topic modeling on the individual segments. The resulting local models are then
combined into a global solution using clustering. The decomposition and
resulting parallelization leads to very fast runtime even on very large
datasets. Our approach furthermore provides insight into how the composition of
topics changes over time and can also be applied using other data partitioning
strategies over any discrete features of the data, such as geographic features
or classes of users. In this paper CLDA is applied successfully to seventeen
years of NIPS conference papers (2,484 documents and 3,280,697 words),
seventeen years of computer science journal abstracts (533,560 documents and
32,551,540 words), and to forty years of the PubMed corpus (4,025,978 documents
and 273,853,980 words).


title:
Ludendorff Coronal Flattening Index of the Total Solar Eclipse on March
  9, 2016

abstract:
  Ludendorff coronal flattening index of the Total Solar Eclipse (TSE) on March
9, 2016, was calculated at various distances in solar radius. As a result, we
obtained the coronal flattening index $\left(\epsilon =a+b\right)$ at a
distance of 2 solar radii is 0.16. The $24^{th}$ solar cycle phase based on the
2016 TSE event obtained -0.64 which showed the corona is pre-minimum type.
Resulted coronal flattening index value gives a predicted maximum amplitude of
the monthly sunspot number ($W_{max}$) for the $25^{th}$ solar cycle to be
$70\pm65$. Therefore, the solar activity for $25^{th}$ solar cycle predicted to
be lower than the current solar cycle, which has a maximum sunspot number value
of 146 in February 2014


title:
Exact probabilities for the indeterminacy of complex networks as
  perceived through press perturbations

abstract:
  We consider the goal of predicting how complex networks respond to chronic
(press) perturbations when characterizations of their network topology and
interaction strengths are associated with uncertainty. Our primary result is
the derivation of exact formulas for the expected number and probability of
qualitatively incorrect predictions about a system's responses under
uncertainties drawn form arbitrary distributions of error. These formulas
obviate the current use of simulations, algorithms, and qualitative modeling
techniques. Additional indices provide new tools for identifying which links in
a network are most qualitatively and quantitatively sensitive to error, and for
determining the volume of errors within which predictions will remain
qualitatively determinate (i.e. sign insensitive). Together with recent
advances in the empirical characterization of uncertainty in ecological
networks, these tools bridge a way towards probabilistic predictions of network
dynamics.


title: Ancient Solutions on Bundles with Non-abelian Structural Group

abstract:
  We generalize the ancient solutions of the Ricci flow on certain principal
${\rm SO}(3)$ bundles over compact quaternionic K\"ahler manifolds constructed
by Bakas, Kong, and Ni to certain $RP^3$ fibre bundles over a product of two
compact quaternionic K\"ahler manifolds. The ancient solutions are of Type I,
$\kappa$-noncollapsed, and have positive Ricci curvature. Analogous solutions
on even-dimensional non-K\"ahlerian bundle spaces are also constructed.


title:
Path discovery by Querying the federation of Relational Database and RDF
  Graph

abstract:
  The class of queries for detecting path is an important as those can extract
implicit binary relations over the nodes of input graphs. Most of the path
querying languages used by the RDF community, like property paths in W3C SPARQL
1.1 and nested regular expressions in nSPARQL are based on the regular
expressions. Federated queries allow for combining graph patterns and
relational database that enables the evaluations over several heterogeneous
data resources within a single query. Federated queries in W3C SPARQL 1.1
currently evaluated over different SPARQL endpoints. In this paper, we present
a federated path querying language as an extension of regular path querying
language for supporting RDF graph integration with relational database. The
federated path querying language is absolutely more expressive than nested
regular expressions and negation-free property paths. Its additional
expressivity can be used for capturing the conjunction and federation of nested
regular path queries. Despite the increase in expressivity, we also show that
federated path queries are still enjoy a low computational complexity and can
be evaluated efficiently.


title:
Knowledge will Propel Machine Understanding of Content: Extrapolating
  from Current Examples

abstract:
  Machine Learning has been a big success story during the AI resurgence. One
particular stand out success relates to unsupervised learning from a massive
amount of data, albeit much of it relates to one modality/type of data at a
time. In spite of early assertions of the unreasonable effectiveness of data,
there is increasing recognition of utilizing knowledge whenever it is available
or can be created purposefully. In this paper, we focus on discussing the
indispensable role of knowledge for deeper understanding of complex text and
multimodal data in situations where (i) large amounts of training data
(labeled/unlabeled) are not available or labor intensive to create, (ii) the
objects (particularly text) to be recognized are complex (i.e., beyond simple
entity-person/location/organization names), such as implicit entities and
highly subjective content, and (iii) applications need to use complementary or
related data in multiple modalities/media. What brings us to the cusp of rapid
progress is our ability to (a) create knowledge, varying from comprehensive or
cross domain to domain or application specific, and (b) carefully exploit the
knowledge to further empower or extend the applications of ML/NLP techniques.
Using the early results in several diverse situations - both in data types and
applications - we seek to foretell unprecedented progress in our ability for
deeper understanding and exploitation of multimodal data.


title: Excited weak bosons and their decays

abstract:
  The weak bosons are bound states of fermions. Here the excitations of the
weak bosons are discussed. Especially we study the decays of these excited
states into weak bosons and photons.


title: EmojiNet: Building a Machine Readable Sense Inventory for Emoji

abstract:
  Emoji are a contemporary and extremely popular way to enhance electronic
communication. Without rigid semantics attached to them, emoji symbols take on
different meanings based on the context of a message. Thus, like the word sense
disambiguation task in natural language processing, machines also need to
disambiguate the meaning or sense of an emoji. In a first step toward achieving
this goal, this paper presents EmojiNet, the first machine readable sense
inventory for emoji. EmojiNet is a resource enabling systems to link emoji with
their context-specific meaning. It is automatically constructed by integrating
multiple emoji resources with BabelNet, which is the most comprehensive
multilingual sense inventory available to date. The paper discusses its
construction, evaluates the automatic resource creation process, and presents a
use case where EmojiNet disambiguates emoji usage in tweets. EmojiNet is
available online for use at http://emojinet.knoesis.org.


title: New frontiers with quantum gases of polar molecules

abstract:
  The field of ultracold quantum matter has burgeoned over the last few
decades, thanks to the growing capabilities for atomic systems to be probed and
manipulated with exquisite control. Researchers can now precisely create and
study quantum many-body states that are effectively isolated from the external
environment. Much of the work in ultracold matter has focused on systems of
alkali or alkaline-earth atoms, mainly due to their ease of cooling. Extending
this precise control to molecules has seen rapidly increasing interest and
activity, as molecules possess additional degrees of freedom that make them
useful for tests of fundamental physics, studying ultracold chemistry and
collisions, and engineering qualitatively new types of quantum phases and
quantum many-body systems. Here, we review one particularly fruitful research
direction: the creation and manipulation of ultracold bialkali molecules. The
recent success in creating a quantum gas of polar molecules opens many exciting
research opportunities.


title: Distributions of $n$th Powers in Finite Fields

abstract:
  In this paper, we first find the distribution of nth power residues modulo a
prime $p$ by analyzing sums involving Dirichlet characters. We then extend this
method to characterize the distribution of powers in arbitrary finite fields.


title: A formula for pi involving nested radicals

abstract:
  We present a new formula for pi involving nested radicals with rapid
convergence. This formula is based on the arctangent function identity with
argument $x=\sqrt{2-{{a}_{k-1}}}/{{a}_{k}}$, where \[
{{a}_{k}}=\underbrace{\sqrt{2+\sqrt{2+\sqrt{2+\cdots
+\sqrt{2}}}}}_{k\,\,\text{square}\,\,\text{roots}} \] is a nested radical
consisting of $k$ square roots. The computational test we performed reveals
that the proposed formula for pi provides a significant improvement in accuracy
as the integer $k$ increases.


title:
probitfe and logitfe: Bias corrections for probit and logit models with
  two-way fixed effects

abstract:
  We present the Stata commands probitfe and logitfe, which estimate probit and
logit panel data models with individual and/or time unobserved effects. Fixed
effect panel data methods that estimate the unobserved effects can be severely
biased because of the incidental parameter problem (Neyman and Scott, 1948). We
tackle this problem by using the analytical and jackknife bias corrections
derived in Fernandez-Val and Weidner (2016) for panels where the two dimensions
($N$ and $T$) are moderately large. We illustrate the commands with an
empirical application to international trade and a Monte Carlo simulation
calibrated to this application.


title:
A local duality principle in derived categories of commutative
  Noetherian rings

abstract:
  Let R be a commutative Noetherian ring. We introduce the notion of
colocalization functors with supports in arbitrary subsets of Spec R, which is
a natural generalization of right derived functors of section functors with
supports in specialization-closed subsets. We prove that the local duality
theorem and the vanishing theorem of Grothendieck type hold for colocalization
functors.


title: Simultaneous diagonalization of vector bundles

abstract:
  Grothendieck-Birkhoff Theorem states that every finite dimensional vector
bundle over the projective line splits as the sum of one dimensional vector
bundles. In this work we study simultaneous splittings of two dimensional
vector bundles over a finite field using the theory of Eichler orders. In the
sheaf-theoretical context, an Eichler order in a matrix algebra is the
intersection of the sheaves of endomorphisms of two vector bundles, so
characterizing split Eichler orders solves the problem of simultaneous
splitting. We caracterize both the genera of Eichler orders containing only
split Eichler orders and the genera containing only a finite number of
non-split classes, in terms of a divisor-valued distance parametrizing the
genera.
  This article shall not be published in its present form. These results will
be included in the article "On genera containing non-split Eichler orders over
function fields" [arXiv:1905.08244].


title:
Distributed and parallel time series feature extraction for industrial
  big data applications

abstract:
  The all-relevant problem of feature selection is the identification of all
strongly and weakly relevant attributes. This problem is especially hard to
solve for time series classification and regression in industrial applications
such as predictive maintenance or production line optimization, for which each
label or regression target is associated with several time series and
meta-information simultaneously. Here, we are proposing an efficient, scalable
feature extraction algorithm for time series, which filters the available
features in an early stage of the machine learning pipeline with respect to
their significance for the classification or regression task, while controlling
the expected percentage of selected but irrelevant features. The proposed
algorithm combines established feature extraction methods with a feature
importance filter. It has a low computational complexity, allows to start on a
problem with only limited domain knowledge available, can be trivially
parallelized, is highly scalable and based on well studied non-parametric
hypothesis tests. We benchmark our proposed algorithm on all binary
classification problems of the UCR time series classification archive as well
as time series from a production line optimization project and simulated
stochastic processes with underlying qualitative change of dynamics.


title: Bias-Aware Sketches

abstract:
  Linear sketching algorithms have been widely used for processing large-scale
distributed and streaming datasets. Their popularity is largely due to the fact
that linear sketches can be naturally composed in the distributed model and be
efficiently updated in the streaming model. The errors of linear sketches are
typically expressed in terms of the sum of coordinates of the input vector
excluding those largest ones, or, the mass on the tail of the vector. Thus, the
precondition for these algorithms to perform well is that the mass on the tail
is small, which is, however, not always the case -- in many real-world datasets
the coordinates of the input vector have a {\em bias}, which will generate a
large mass on the tail.
  In this paper we propose linear sketches that are {\em bias-aware}. We
rigorously prove that they achieve strictly better error guarantees than the
corresponding existing sketches, and demonstrate their practicality and
superiority via an extensive experimental evaluation on both real and synthetic
datasets.


title: New results for traitor tracing schemes

abstract:
  In the last two decades, several classes of codes are introduced to protect
the copyrighted digital data. They have important applications in the scenarios
like digital fingerprinting and broadcast encryption schemes. In this paper we
will discuss three important classes of such codes, namely, frameproof codes,
parent-identifying codes and traceability codes.
  Firstly, suppose $N(t)$ is the minimal integer such that there exists a
binary $t$-frameproof code of length $N$ with cardinality larger than $N$, we
prove that $N(t)\ge\frac{15+\sqrt{33}}{24} (t-2)^2$, which is a great
improvement of the previously known bound $N(t)\ge\binom{t+1}{2}$. Moreover, we
find that the determination of $N(t)$ is closely related to a conjecture of
Erd\H{o}s, Frankl and F\"uredi posed in the 1980's, which implies the
conjectured value $N(t)=t^2+o(t^2)$. Secondly, we derive a new upper bound for
parent-identifying codes, which is superior than all previously known bounds.
Thirdly, we present an upper bound for 3-traceability codes, which shows that a
$q$-ary 3-traceability code of length $N$ can have at most $cq^{\lceil
N/9\rceil}$ codewords, where $c$ is a constant only related to the code length
$N$. It is the first meaningful upper bound for 3-traceability codes and our
result supports a conjecture of Blackburn et al. posed in 2010.


title: Evaluation of the general 3-loop vacuum Feynman integral

abstract:
  We discuss the systematic evaluation of 3-loop vacuum integrals with
arbitrary masses. Using integration by parts, the general integral of this type
can be reduced algebraically to a few basis integrals. We define a set of
modified finite basis integrals that are particularly convenient for expressing
renormalized quantities. The basis integrals can be computed numerically by
solving coupled first-order differential equations, using as boundary
conditions the analytically known special cases that depend on only one mass
scale. We provide the results necessary to carry this out, and introduce an
implementation in the form of a public software package called 3VIL (3-loop
Vacuum Integral Library), which efficiently computes the numerical values of
the basis integrals for any specified masses. 3VIL is written in C, and can be
linked from C, C++, or FORTRAN code.


title:
Reduction of the low-temperature bulk gap in samarium hexaboride under
  high magnetic fields

abstract:
  SmB$_6$ exhibits a small (15-20 meV) bandgap at low temperatures due to
hybridized $d$ and $f$ electrons, a tiny (3 meV) transport activation energy
$(E_{A})$ above 4 K, and surface states accessible to transport below 2 K. We
study its magnetoresistance in 60-T pulsed fields between 1.5 K and 4 K. The
response of the nearly $T$-independent surface states (which show no
Shubnikov-de Haas oscillations) is distinct from that of the activated bulk.
$E_{A}$ shrinks by 50% under fields up to 60 T. Data up to 93 T suggest that
this trend continues beyond 100 T, in contrast with previous explanations. It
rules out emerging theories to explain observed exotic magnetic quantum
oscillations.


title:
Sparse Hierarchical Tucker Factorization and its Application to
  Healthcare

abstract:
  We propose a new tensor factorization method, called the Sparse
Hierarchical-Tucker (Sparse H-Tucker), for sparse and high-order data tensors.
Sparse H-Tucker is inspired by its namesake, the classical Hierarchical Tucker
method, which aims to compute a tree-structured factorization of an input data
set that may be readily interpreted by a domain expert. However, Sparse
H-Tucker uses a nested sampling technique to overcome a key scalability problem
in Hierarchical Tucker, which is the creation of an unwieldy intermediate dense
core tensor; the result of our approach is a faster, more space-efficient, and
more accurate method. We extensively test our method on a real healthcare
dataset, which is collected from 30K patients and results in an 18th order
sparse data tensor. Unlike competing methods, Sparse H-Tucker can analyze the
full data set on a single multi-threaded machine. It can also do so more
accurately and in less time than the state-of-the-art: on a 12th order subset
of the input data, Sparse H-Tucker is 18x more accurate and 7.5x faster than a
previously state-of-the-art method. Even for analyzing low order tensors (e.g.,
4-order), our method requires close to an order of magnitude less time and over
two orders of magnitude less memory, as compared to traditional tensor
factorization methods such as CP and Tucker. Moreover, we observe that Sparse
H-Tucker scales nearly linearly in the number of non-zero tensor elements. The
resulting model also provides an interpretable disease hierarchy, which is
confirmed by a clinical expert.


title:
K-theoretic Gromov--Witten invariants in genus 0 and integrable
  hierarchies

abstract:
  We prove that the genus-0 invariants in K-theoretic Gromov--Witten theory are
governed by an integrable hierarchy of hydrodynamic type. If the K-theoretic
quantum product is semisimple, then we also prove the completeness of the
hierarchy.


title:
Matroidal Structure of Skew Polynomial Rings with Application to Network
  Coding

abstract:
  Over a finite field $\mathbb{F}_{q^m}$, the evaluation of skew polynomials is
intimately related to the evaluation of linearized polynomials. This connection
allows one to relate the concept of polynomial independence defined for skew
polynomials to the familiar concept of linear independence for vector spaces.
This relation allows for the definition of a representable matroid called the
$\mathbb{F}_{q^m}[x;\sigma]$-matroid, with rank function that makes it a metric
space. Specific submatroids of this matroid are individually bijectively
isometric to the projective geometry of $\mathbb{F}_{q^m}$ equipped with the
subspace metric. This isometry allows one to use the
$\mathbb{F}_{q^m}[x;\sigma]$-matroid in a matroidal network coding application.


title:
Universal scaling for recovery of Fourier's law in low-dimensional
  solids under momentum conservation

abstract:
  Dynamic renormalization group (RG) of fluctuating viscoelastic equations is
investigated to clarify the cause for numerically reported disappearance of
anomalous heat conduction (recovery of Fourier's law) in low-dimensional
momentum-conserving systems. RG flow is obtained explicitly for simplified two
model cases: a one-dimensional continuous medium under low pressure and
incompressible viscoelastic medium of arbitrary dimensions. Analyses of these
clarify that the inviscid fixed point of contributing the anomalous heat
conduction becomes unstable under the RG flow of nonzero elastic-wave speeds.
The dynamic RG analysis further predicts a universal scaling of describing the
crossover between the growth and saturation of observed heat conductivity,
which is confirmed through the numerical experiments of Fermi-Pasta-Ulam
$\beta$ (FPU-$\beta$) lattices.


title: Solving the Dual Problems of Dynamic Programs via Regression

abstract:
  In recent years, information relaxation and duality in dynamic programs have
been studied extensively, and the resulted primal-dual approach has become a
powerful procedure in solving dynamic programs by providing lower-upper bounds
on the optimal value function. Theoretically, with the so called value-based
optimal dual penalty, the optimal value function could be recovered exactly via
strong duality. However, in practice, obtaining tight dual bounds usually
requires good approximations of the optimal dual penalty, which could be
time-consuming due to the conditional expectations that need to be estimated
via nested simulation. In this paper, we will develop a framework of regression
approach to approximating the optimal dual penalty in a non-nested manner, by
exploring the structure of the function space consisting of all feasible dual
penalties. The resulted approximations maintain to be feasible dual penalties,
and thus yield valid dual bounds on the optimal value function. We show that
the proposed framework is computationally efficient, and the resulted dual
penalties lead to numerically tractable dual problems. Finally, we apply the
framework to a high-dimensional dynamic trading problem to demonstrate its
effectiveness in solving the dual problems of complex dynamic programs.


title: Delocalization of a $(1+1)$-dimensional stochastic wave equation

abstract:
  A noteworthy property of many parabolic stochastic PDEs is that they locally
linearize (Foondun, Khoshnevisan and Mahboubi (2015), Hairer (2013, 2014),
Hairer and Pardoux (2015), Khoshnevisan, Swanson, Xiao and Zhang (2013)). We
prove that, by contrast, a large family of stochastic wave equations in
dimension one do not possess this important property.


title: Camera Fingerprint: A New Perspective for Identifying User's Identity

abstract:
  Identifying user's identity is a key problem in many data mining
applications, such as product recommendation, customized content delivery and
criminal identification. Given a set of accounts from the same or different
social network platforms, user identification attempts to identify all accounts
belonging to the same person. A commonly used solution is to build the
relationship among different accounts by exploring their collective patterns,
e.g., user profile, writing style, similar comments. However, this kind of
method doesn't work well in many practical scenarios, since the information
posted explicitly by users may be false due to various reasons. In this paper,
we re-inspect the user identification problem from a novel perspective, i.e.,
identifying user's identity by matching his/her cameras. The underlying
assumption is that multiple accounts belonging to the same person contain the
same or similar camera fingerprint information. The proposed framework, called
User Camera Identification (UCI), is based on camera fingerprints, which takes
fully into account the problems of multiple cameras and reposting behaviors.


title: Derandomization for k-submodular maximization

abstract:
  Submodularity is one of the most important property of combinatorial
optimization, and $k$-submodularity is a generalization of submodularity.
Maximization of $k$-submodular function is NP-hard, and approximation
algorithms are studied. For monotone $k$-submodular function, [Iwata, Tanigawa,
and Yoshida 2016] gave $k/(2k-1)$-approximation algorithm. In this paper, we
give a deterministic algorithm by derandomizing that algorithm. Derandomization
scheme is from [Buchbinder and Feldman 2016]. Our algorithm is
$k/(2k-1)$-approximation and polynomial-time algorithm.


title:
Supersymmetric models on magnetized orbifolds with flux-induced
  Fayet-Iliopoulos terms

abstract:
  We study supersymmetric (SUSY) models derived from the ten-dimensional SUSY
Yang- Mills theory compactified on magnetized orbifolds, with nonvanishing
Fayet-Iliopoulos (FI) terms induced by magnetic fluxes in extra dimensions.
Allowing the presence of FI-terms relaxes a constraint on flux configurations
in SUSY model building based on magnetized backgrounds. In this case, charged
fields develop their vacuum expectation values (VEVs) to cancel the FI-terms in
the D-flat directions of fluxed gauge symmetries, which break the gauge
symmetries and lead to a SUSY vacuum. Based on this idea, we propose a new
class of SUSY magnetized orbifold models with three generations of quarks and
leptons. Especially, we construct a model where the right-handed sneutrinos
develop their VEVs which restore the supersymmetry but yield lepton number
violating terms below the compactification scale, and show their
phenomenological consequences.


title: Spacious knots

abstract:
  We show that there exist hyperbolic knots in the 3-sphere such that the set
of points of large injectivity radius in the complement take up the bulk of the
volume. More precisely, given a finite volume hyperbolic manifold, for any
bound R>0 on injectivity radius, consider the set of points with injectivity
radius at least R; we call this the R-thick part of the manifold. We show that
for any $\epsilon>0$, there exists a knot K in the 3-sphere so that the ratio
of the volume of the R-thick part of the knot complement to the volume of the
knot complement is at least $1-\epsilon$. As R approaches infinity, and as
$\epsilon$ approaches zero, this gives a sequence of knots that is said to
Benjamini--Schramm converge to hyperbolic space. This answers a question of
Brock and Dunfield.


title: Online Event Integration with StoryPivot

abstract:
  Modern data integration systems need to process large amounts of data from a
variety of data sources and with real-time integration constraints. They are
not only employed in enterprises for managing internal data but are also used
for a variety of web services that use techniques such as entity resolution or
data cleaning in live systems. In this work, we discuss a new generation of
data integration systems that operate on (un-)structured data in an online
setting, i.e., systems which process continuously modified datasets upon which
the integration task is based. We use as an example of such a system an online
event integration system called StoryPivot. It observes events extracted from
news articles in data sources such as the 'Guardian' or the 'Washington Post'
which are integrated to show users the evolution of real-world stories over
time. The design decisions for StoryPivot are influenced by the trade-off
between maintaining high quality integration results while at the same time
building a system that processes and integrates events in near real-time. We
evaluate our design decisions with experiments on two real-world datasets and
generalize our findings to other data integration tasks that have a similar
system setup.


title: Approximate cross-validation formula for Bayesian linear regression

abstract:
  Cross-validation (CV) is a technique for evaluating the ability of
statistical models/learning systems based on a given data set. Despite its wide
applicability, the rather heavy computational cost can prevent its use as the
system size grows. To resolve this difficulty in the case of Bayesian linear
regression, we develop a formula for evaluating the leave-one-out CV error
approximately without actually performing CV. The usefulness of the developed
formula is tested by statistical mechanical analysis for a synthetic model.
This is confirmed by application to a real-world supernova data set as well.


title:
Particle path(s) through a nested Mach-Zehnder interferometer: Reply to
  Griffiths

abstract:
  Griffiths [Phys. Rev. A 94, 032115 (2016)] analyzed, in the framework of
consistent histories interpretation, the controversy regarding the approach to
the past of a quantum particle introduced by Vaidman [Phys. Rev. A 87, 052104
(2013)]. I argue that Griffith's criticism of my approach using analysis of
experiments with weak probes is unfounded.


title: A parallel framework for reverse search using mts

abstract:
  We describe mts, which is a generic framework for parallelizing certain types
of tree search programs, that (a) provides a single common wrapper containing
all of the parallelization, and (b) minimizes the changes needed to the
existing single processor legacy code. The mts code was derived from ideas used
to develop mplrs, a parallelization of the reverse search vertex enumeration
code lrs. The tree search properties required for the use of mts are satisfied
by any reverse search algorithm as well as other tree search methods such as
backtracking and branch and bound. mts is programmed in C, uses the MPI
parallel environment, and can be run on a network of computers.
  As examples we parallelize two simple existing reverse search codes:
generating topological orderings and generating spanning trees of a graph. We
give computational results comparing the parallel codes with state of the art
sequential codes for the same problems.


title: Construction of MDS self-dual codes from orthogonal matrices

abstract:
  In this paper, we give algorithms and methods of construction of self-dual
codes over finite fields using orthogonal matrices. Randomization in the
orthogonal group, and code extension are the main tools. Some optimal, almost
MDS, and MDS self-dual codes over both small and large prime fields are
constructed.


title: Categorical Complexity

abstract:
  We introduce a notion of complexity of diagrams (and in particular of objects
and morphisms) in an arbitrary category, as well as a notion of complexity of
functors between categories equipped with complexity functions. We discuss
several examples of this new definition in categories of wide common interest,
such as finite sets, Boolean functions, topological spaces, vector spaces,
semi-linear and semi-algebraic sets, graded algebras, affine and projective
varieties and schemes, and modules over polynomial rings. We show that on one
hand categorical complexity recovers in several settings classical notions of
non-uniform computational complexity (such as circuit complexity), while on the
other hand it has features which make it mathematically more natural. We also
postulate that studying functor complexity is the categorical analog of
classical questions in complexity theory about separating different complexity
classes.


title: The effects of spatiotemporal coherence on interferometric imaging

abstract:
  Illumination coherence plays a major role in various imaging systems, from
microscopy, metrology, digital holography, optical coherence tomography, to
ultrasound imaging. Here, we present a systematic study on the effects of
degrees of spatiotemporal coherence of an illumination (DSTCI) on imaging
quality. An optical field with arbitrary DSTCI was decomposed into wavelets
with constituent spatiotemporal frequencies, and the effects on image quality
were quantitatively investigated. The results show the synergistic effects on
reduction of speckle noise when DSTCI is decreased. This study presents a
method to systematically control DSTCI, and the result provides an essential
reference on the effects of DSTCI on imaging quality. We believe that the
presented methods and results can be implemented in various imaging systems for
characterising and improving imaging quality.


title: A classification of continuous wavelet transforms in dimension three

abstract:
  This paper presents a full catalogue, up to conjugacy and subgroups of finite
index, of all matrix groups $H < {\rm GL}(3,\mathbb{R})$ that give rise to a
continuous wavelet transform with associated irreducible quasi-regular
representation. For each group in this class, coorbit theory allows to
consistently define spaces of sparse signals, and to construct atomic
decompositions converging simultaneously in a whole range of these spaces. As
an application of the classification, we investigate the existence of compactly
supported admissible vectors and atoms for the groups.


title:
MIMO Multiway Distributed-Relay Channel with Full Data Exchange: An
  Achievable Rate Perspective

abstract:
  We consider efficient communications over the multiple-input multiple-output
(MIMO) multiway distributed relay channel (MDRC) with full data exchange, where
each user, equipped with multiple antennas, broadcasts its message to all the
other users via the help of a number of distributive relays. We propose a
physical-layer network coding (PNC) based scheme involving linear precoding for
channel alignment nested lattice coding for PNC, and lattice-based precoding
for interference mitigation, We show that, with the proposed scheme,
distributed relaying achieves the same sum-rate as cooperative relaying in the
high SNR regime. We also show that the proposed scheme achieve the asymptotic
sum capacity of the MIMO MDRC within a constant gap at high SNR. Numerical
results demonstrate that the proposed scheme considerably outperforms the
existing schemes including decode-and-forward and amplify-and-forward.


title:
Potentials and Challenges of Light Fidelity Based Indoor Communication
  System

abstract:
  In this era of modern devices and high speed communication the issue of
spectral overloading is increasing with time and becoming more serious. With
the advancement in LED industry, light fidelity (Li-Fi) based indoor network is
an attractive substitute for the existing radio frequency (RF) based
communication networks. Because of its capability to perform dual function of
lighting as well as high speed communication, Li-Fi is attracting both
industrial as well as academic researchers. The Li-Fi networking paradigm
offers performance enhancements which can make it an attractive backup option
to be used for networking setup in Internet of things (IOT) and its indoor
capabilities make it an attractive choice for large scale indoor communication
in next generation wireless networking environment. This paper discusses key
potentials of Li-Fi based indoor communication system and point out the
challenges which indoor based Li-Fi network is facing under the knowledge of
existing research work in the field of Li-Fi.


title:
Large Magnetocaloric effect and magnetic phase transitions in
  Nd$_2$NiMnO$_6$

abstract:
  We present combined experimental and theoretical investigations on the
magnetic and magnetocaloric behavior of Nd$_2$NiMnO$_6$. The relative cooling
power (RCP) which quantifies the usefulness of a magnetocaloric (MC) material
is estimated to be $\approx 300$ J/Kg near the ferromagnetic transition at $T_C
\approx 195$ K. This RCP is comparable to the best known MC materials.
Additionally, the magnetic entropy change has a broad profile ($T_C - 50~{\rm
K} < T < T_C + 50~{\rm K}$) leading to an enhancement in the working-range of
temperatures for magnetocaloric based cooling. These features make
Nd$_2$NiMnO$_6$ a superior magnetocaloric material compared for example, to the
nonmagnetic counterpart Y$_2$NiMnO$_6$. We identify the mechanism for the
enhanced RCP which can guide search for future MC materials.