Agreed. Our reasoning for for contributing straight to Flink was we plan on doing a lot of wierd monkey-ing around with these things, and were going to have to get our hands dirty with some code eventually anyway. The LSTM isn't *that* difficult to implement, and it seems easier to write our own than to understand someone else's insanity.
The plan is to get a 'basic' version going, then start tweaking the special cases. We have a use case for bi-directional, but it's not our primary motivation. I have no problem exposing new flavors as we make them. tg Trevor Grant Data Scientist https://github.com/rawkintrevo http://stackexchange.com/users/3002022/rawkintrevo http://trevorgrant.org *"Fortunate is he, who is able to know the causes of things." -Virgil* On Fri, Feb 12, 2016 at 7:51 AM, Suneel Marthi <suneel.mar...@gmail.com> wrote: > On Fri, Feb 12, 2016 at 8:45 AM, Trevor Grant <trevor.d.gr...@gmail.com> > wrote: > > > Hey all, > > > > I had a post a while ago about needing neural networks. We specifically > > need a very special type that are good for time series/sensors called > > LSTM. We had a talk about pros/cons of using deeplearning4j for this use > > case and eventually decided it made more sense to implement in native > Flink > > for our use case. > > > > So, this is somewhat relevant to what Theodore just said, but different > > enough that I wanted a separate thread. > > > > "Focusing on Flink does well and implement algorithms built around > inherent > > advantages..." > > > > One thing that jumps to mind is doing online learning. The batch nature > of > > all of the other 'big boys' means that they are by definition going to > > always be offline modes. > > > > Also, even though LTSMs are somewhat of a corner case in the NN world, > the > > streaming nature of Flink (a sequence of data) makes fairly relevant to > > people who would be using Flink in the first place (? IMHO) > > > > Finally, there should be some positive externalities that come from this > > such as a back propegation algorithm, which should then be reusable for > > things like HMMs. > > > > So at any rate, the research Spike for me started earlier this week- I > hope > > to start cutting some scala code over the weekend or beginning of next > > week. Also I'm asking to check out FLINK-2259 because I need some sort of > > functionality like that before I get started, and I could use the git > > practice. > > > > Idk if there is any interest in adding this or if you want to make a JIRA > > for LTSM neural nets (or if I should write one, with appropriate papers > > cited, as seems to be the fashion), or maybe wait and see what I end up > > with? > > > > It would be good if we also supported Bidirectional LSTMs. > > http://www.cs.toronto.edu/~graves/asru_2013.pdf > > http://www.cs.toronto.edu/~graves/phd.pdf > > > > > > Also- I'll probably be blowing you up with questions. > > > > Best, > > > > tg > > > > > > > > Trevor Grant > > Data Scientist > > https://github.com/rawkintrevo > > http://stackexchange.com/users/3002022/rawkintrevo > > http://trevorgrant.org > > > > *"Fortunate is he, who is able to know the causes of things." -Virgil* > > >
