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improved stochastic optimization algorithms\r\nGeneralized tasks to 3D tensors\r\nMore unit tests\r\nImproved command line utilities and 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& clarify the implementation of the stochastic optimizers:\r\n* have the parameter smoothing optional (see loop.h)\r\n* explicit stochastic & batch problems passed\r\n* always update the batch values (value, gradient) after each epoch\r\n* thus can check for convergence after each epoch using a given epsilon\r\n* extend the learning rate schedule to: fixed, exponential decay, t-inverse (see the SVRG paper - experimentation section)"},"comment":{"url":"https://api.github.com/repos/accosmin/nano/issues/comments/262481611","html_url":"https://github.com/accosmin/nano/issues/137#issuecomment-262481611","issue_url":"https://api.github.com/repos/accosmin/nano/issues/137","id":262481611,"user":{"login":"accosmin","id":11867946,"avatar_url":"https://avatars.githubusercontent.com/u/11867946?v=3","gravatar_id":"","url":"https://api.github.com/users/accosmin","html_url":"https://github.com/accosmin","followers_url":"https://api.github.com/users/accosmin/followers","following_url":"https://api.github.com/users/accosmin/following{/other_user}","gists_url":"https://api.github.com/users/accosmin/gists{/gist_id}","starred_url":"https://api.github.com/users/accosmin/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/accosmin/subscriptions","organizations_url":"https://api.github.com/users/accosmin/orgs","repos_url":"https://api.github.com/users/accosmin/repos","events_url":"https://api.github.com/users/accosmin/events{/privacy}","received_events_url":"https://api.github.com/users/accosmin/received_events","type":"User","site_admin":false},"created_at":"2016-11-23T10:43:51Z","updated_at":"2016-11-23T10:43:51Z","body":"SG/SGM should never fail during benchmark_stoch for convex functions."}}
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