{"action":"created","issue":{"url":"https://api.github.com/repos/dmlc/MXNet.jl/issues/29","labels_url":"https://api.github.com/repos/dmlc/MXNet.jl/issues/29/labels{/name}","comments_url":"https://api.github.com/repos/dmlc/MXNet.jl/issues/29/comments","events_url":"https://api.github.com/repos/dmlc/MXNet.jl/issues/29/events","html_url":"https://github.com/dmlc/MXNet.jl/issues/29","id":117165657,"number":29,"title":"Online/temporal learning","user":{"login":"tbreloff","id":933338,"avatar_url":"https://avatars.githubusercontent.com/u/933338?v=3","gravatar_id":"","url":"https://api.github.com/users/tbreloff","html_url":"https://github.com/tbreloff","followers_url":"https://api.github.com/users/tbreloff/followers","following_url":"https://api.github.com/users/tbreloff/following{/other_user}","gists_url":"https://api.github.com/users/tbreloff/gists{/gist_id}","starred_url":"https://api.github.com/users/tbreloff/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tbreloff/subscriptions","organizations_url":"https://api.github.com/users/tbreloff/orgs","repos_url":"https://api.github.com/users/tbreloff/repos","events_url":"https://api.github.com/users/tbreloff/events{/privacy}","received_events_url":"https://api.github.com/users/tbreloff/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":3,"created_at":"2015-11-16T16:40:51Z","updated_at":"2015-11-16T20:26:06Z","closed_at":null,"body":"Is it possible to update a model fit one data point at a time?  More importantly, in what capacity is real-time time series analysis supported?  Most/all of the examples are focused on static datasets with batch fitting, but I'm not sure if that's the only way to do it with MXNet.\r\n\r\nSome topics that I'm interested in:\r\n- LSTM-g\r\n- HTM (Heirarchical Temporal Memory)\r\n- Spiking RNNs\r\n- Reservoir Computing (Liquid State Machines)\r\n\r\nwith applications in:\r\n- Video sequence analysis\r\n- Auditory processing\r\n- Semantic analysis\r\n- Data stream sequencing, non-linear econometrics\r\n\r\nTo what extent are any of these possible through MXNet?  (Even if it's not possible today, would the framework support them naturally?)  I would consider contributing some algorithms here, or creating standalone packages that could be used by MXNet or my experimental package: [OnlineAI.jl](https://github.com/tbreloff/OnlineAI.jl).  If the MXNet framework does not support these topics naturally, I'll probably just continue to develop my OnlineAI framework independently."},"comment":{"url":"https://api.github.com/repos/dmlc/MXNet.jl/issues/comments/157159362","html_url":"https://github.com/dmlc/MXNet.jl/issues/29#issuecomment-157159362","issue_url":"https://api.github.com/repos/dmlc/MXNet.jl/issues/29","id":157159362,"user":{"login":"pluskid","id":3542,"avatar_url":"https://avatars.githubusercontent.com/u/3542?v=3","gravatar_id":"","url":"https://api.github.com/users/pluskid","html_url":"https://github.com/pluskid","followers_url":"https://api.github.com/users/pluskid/followers","following_url":"https://api.github.com/users/pluskid/following{/other_user}","gists_url":"https://api.github.com/users/pluskid/gists{/gist_id}","starred_url":"https://api.github.com/users/pluskid/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/pluskid/subscriptions","organizations_url":"https://api.github.com/users/pluskid/orgs","repos_url":"https://api.github.com/users/pluskid/repos","events_url":"https://api.github.com/users/pluskid/events{/privacy}","received_events_url":"https://api.github.com/users/pluskid/received_events","type":"User","site_admin":false},"created_at":"2015-11-16T20:26:06Z","updated_at":"2015-11-16T20:26:06Z","body":"In terms of rnn lstm API plan: I might be the person to work on that but I do not have a clear time line. I'm planning to look around what kind of interfaces the existing popular libraries are using for support recurrent neural networks. I might have larger chunk of free time to look at it during winter holidays. \r\n\r\nBut if you are willing to help out, you are definitely very welcome to contribute your expertise in this domain to MXNet.jl. :)"}}