we are talking about binary operators, so these are combinations of types, but for most part, yes, this is currently working poorly for most part for combinations including at least one sparse operand type.
On Wed, Sep 10, 2014 at 11:54 AM, peng <[email protected]> wrote: > Is it mostly sparse or non-sparse? Both of them are single-node library so > they seems not possible to use directly. > > > On 09/10/2014 01:29 PM, Dmitriy Lyubimov 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> >>> >>> >
