W1: The proposed method is a combination of existing loss. The novelty of technical contribution is not very strong.
W2: The proposed hybrid loss is argued that it is beneficial as the Proxy-NCA loss will promotes learning new knowledge better (first paragraph in Sec. 3.4), rather than less catastrophic forgetting. But the empirical results show that the proposed method exhibits much less forgetting than the prior arts (Table. 2). The argument and the empirical results are not well aligned.
Also, as the proposed method seems promoting learning new knowledge, it is suggested to empirically validate the benefit of the proposed approach by a measure to evaluate the ability to learn new knowledge (e.g., intransigence (Chaudhry et al., 2018)).
W3: Missing important comparison to Ahn et al.'s method in Table 3 (and corresponding section, titled "comparison with Logits Bias Solutions for Conventional CIL setting").
W4: Missing analyses of ablated models (Table 4). The proposed hybrid loss exhibits meaningful empirical gains only in CIFAR100 (and marginal gain in CIFAR10), comparing "MS loss with NCM (Gen)" and "Hybrid loss with NCM (Gen)". But there is no descriptive analysis for it.
W5: Lack of details of Smooth datasets in Sec. 4.3.
W6: Missing some citation (or comparison) using logit bias correction in addition to Wu et al., 2019 and Anh et al., 2020
Kang et al., 2020: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9133417
Mittal et al., 2021: https://openaccess.thecvf.com/content/CVPR2021W/CLVision/papers/Mittal_Essentials_for_Class_Incremental_Learning_CVPRW_2021_paper.pdf
W7: Unclear arguments or arguments lack of supporting facts
4th para in Sec.1
'It should be noticed that in online CIL setting the data is seen only once, not fully trained, so it is analogous to the low data regime in which the generative classifier is preferable.' Why?
5th line of 2nd para in Sec. 3.1.3
'This problem becomes more severe as the the number of classes increases.'
Lack of supporting facts
W8: Some mistakes in text (see details in notes below) and unclear presentations Note
Mistakes in text
End of 1st para in Sec.1: intelligence agents -> intelligent agents
3th line of 1 para in Sec. 3.2: we can inference with -> we can conduct inference with
1st line of 1st para in Sec. 3.3
we choose MS loss as training... -> we choose the MS loss as a training...
MS loss is a state-of... -> MS loss is the state-of...
6th line of Proposition 1: 'up to an additive constant and L' -> 'up to an additive constant c and L'
Improvement ideas in presentations
Fig. 1: texts in legends and axis labels should be larger
At the beginning of page 6: Proposition (1) -> Proposition 1. --> (1) is confused with Equation 1.
Captions and legend's font should be larger (similar to text size) in Fig. 2 and 3.
1: texts in legends and axis labels should be larger At the beginning of page 6: Proposition (1) -> Proposition 1. --> (1) is confused with Equation 1. Captions and legend's font should be larger (similar to text size) in Fig. 2 and 3.