{"action":"created","issue":{"url":"https://api.github.com/repos/lessthanoptimal/ejml/issues/17","repository_url":"https://api.github.com/repos/lessthanoptimal/ejml","labels_url":"https://api.github.com/repos/lessthanoptimal/ejml/issues/17/labels{/name}","comments_url":"https://api.github.com/repos/lessthanoptimal/ejml/issues/17/comments","events_url":"https://api.github.com/repos/lessthanoptimal/ejml/issues/17/events","html_url":"https://github.com/lessthanoptimal/ejml/issues/17","id":185275895,"number":17,"title":"Sparse Matrix","user":{"login":"mroodschild","id":3471882,"avatar_url":"https://avatars.githubusercontent.com/u/3471882?v=3","gravatar_id":"","url":"https://api.github.com/users/mroodschild","html_url":"https://github.com/mroodschild","followers_url":"https://api.github.com/users/mroodschild/followers","following_url":"https://api.github.com/users/mroodschild/following{/other_user}","gists_url":"https://api.github.com/users/mroodschild/gists{/gist_id}","starred_url":"https://api.github.com/users/mroodschild/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mroodschild/subscriptions","organizations_url":"https://api.github.com/users/mroodschild/orgs","repos_url":"https://api.github.com/users/mroodschild/repos","events_url":"https://api.github.com/users/mroodschild/events{/privacy}","received_events_url":"https://api.github.com/users/mroodschild/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2016-10-26T01:39:37Z","updated_at":"2016-10-28T14:03:03Z","closed_at":null,"body":"Hello!\r\nCurrently I was reviewing many libraries. EJML, is by far the easiest and best designed. I think EJML, can become very accepted if contemplates Sparse Matrices, as they are widely used by the scientific community. Moreover, when the deep neural networks make heavy use of sparse matrices.\r\nThanks"},"comment":{"url":"https://api.github.com/repos/lessthanoptimal/ejml/issues/comments/256928023","html_url":"https://github.com/lessthanoptimal/ejml/issues/17#issuecomment-256928023","issue_url":"https://api.github.com/repos/lessthanoptimal/ejml/issues/17","id":256928023,"user":{"login":"mroodschild","id":3471882,"avatar_url":"https://avatars.githubusercontent.com/u/3471882?v=3","gravatar_id":"","url":"https://api.github.com/users/mroodschild","html_url":"https://github.com/mroodschild","followers_url":"https://api.github.com/users/mroodschild/followers","following_url":"https://api.github.com/users/mroodschild/following{/other_user}","gists_url":"https://api.github.com/users/mroodschild/gists{/gist_id}","starred_url":"https://api.github.com/users/mroodschild/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mroodschild/subscriptions","organizations_url":"https://api.github.com/users/mroodschild/orgs","repos_url":"https://api.github.com/users/mroodschild/repos","events_url":"https://api.github.com/users/mroodschild/events{/privacy}","received_events_url":"https://api.github.com/users/mroodschild/received_events","type":"User","site_admin":false},"created_at":"2016-10-28T14:03:03Z","updated_at":"2016-10-28T14:03:03Z","body":"Currently when working with deep networks, the coefficient sparse in a autoencoder, causes the outputs of the hidden layer are sparse, this output enters the next layer with a lot of zeros, depending on this ratio, 95% or 90% values are zero, and these are multiplied by dense matrices of the next layer. We can not say that there is a regular form of zeros, but it is important to have some generic multiplication operation.\r\n\r\nThanks for the info, I'll check matrix and the library.\r\n"}}
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