Hi Dmitriy, Did you mean something like implementing *"Strassen algorithm"* for matrix multiplication?
thanks & best regards, Ankit On Wed, Sep 10, 2014 at 10:59 PM, Dmitriy Lyubimov <[email protected]> wrote: > The biggest problem today (in my opinion) is mahout-math. > > (1) cost/type based optimization of matrix-matrix multiplication > (2) cost/type based optimization of elementwise matrix-matrix operations > > There is already some work done there, especially in the realm of > vector-vector opreations, so matrix-matrix operations that work with > matrices backed by a set of vectors, should naturally benefit from that. > > Other two noble goals have been: > > (3) jBLAS backed matrices, including a part of (1) and (2) > (4) JCuda backed matrices, including as a part of (1) and (2) > > Otherwise, if you are interested in writing yet-another quasi-algebraic > solver methodology, it is a second priority but would be welcome provided > you provide references to principled approach and its adaptation to scaled > operations strategy, for review, and as long as long as preferrably this > method is not yet part of MLib in spark. > > -d > > > > On Wed, Sep 10, 2014 at 10:14 AM, Ankit Sharma < > [email protected]> > wrote: > > > Hello, > > > > I have been an user of Mahout for quite sometime now and got really > exited > > when I heard mahout is moving to Spark. Today I played around with Linear > > Regression example and browsed some of the spark Machine Learning(ML) > code. > > It was really interesting to see how intuitive the entire process is. > > > > I have background in data science model building and I would like to > > contribute in the development process. So, I would like to get some > advice > > on what has already been completed on ML side and from where I can start? > > > > I have couple of ideas like I can start with either some classification > > algorithm like SVM or build(enhance) some simple building blocks. You can > > throw in your suggestions and I'll be see which one falls into my domain, > > and try to work on them. > > > > thanks & best regards, > > > > Ankit Sharma > > Data Science Professional > > _______________________ > > Mobile: +91-9632383141 > > Email: [email protected] > > Skype: aksharma11588 > > LinkedIn <http://in.linkedin.com/in/aks11588/> | Digg Data > > <http://www.diggdata.in/> | about.me <http://about.me/ankitksharma> > > >
