btw I think Mahout sparse matrix should be fairly efficient when handling diagonal and triangular or Hessenberg like stuff.
On Mon, Jan 16, 2012 at 11:18 AM, Dmitriy Lyubimov <[email protected]> wrote: > yes, the UpperTriangular in SSVD doesn't support some of the Matrix > operations. On top of it, it is built with some assumptions that > Mahout support in general should not have, or have an alternative for, > for efficiency sake of ssvd: > > 1) it assumes the matrix is dense. > 2) most importantly, it assumes the matrix is sufficiently small (it > packs it into a single vector). that means it may experience problems > when dense allocation exceeds 2G contiguous heap chunk. > 3) consequently, it only serializes into a dense vector. > > for diagonal matrices, the same ssvd uses vector form. It does mean > that you don't have a nice single method to implement multiplication; > but it is just one vector-scalar loop instead, but oh well. > > -d > > On Sat, Jan 14, 2012 at 2:03 AM, Tamas Jambor <[email protected]> wrote: >> thanks, ideally I would need both symmetric and diagonal. >> >> On Sat, Jan 14, 2012 at 8:26 AM, Sebastian Schelter <[email protected]> wrote: >> >>> I think Tamas referred to matrices that are symmetric (only the upper >>> triangular half would need to be stored) not diagonal matrices. >>> >>> >>> On 14.01.2012 05:25, Lance Norskog wrote: >>> > org.apache.mahout.math.DiagonalMatrix >>> > >>> > It even supports sparse values in the diagonal! >>> > >>> > On Fri, Jan 13, 2012 at 9:00 AM, Tamas Jambor (Commented) (JIRA) >>> > <[email protected]> wrote: >>> >> >>> >> [ >>> https://issues.apache.org/jira/browse/MAHOUT-737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13185670#comment-13185670] >>> >> >>> >> Tamas Jambor commented on MAHOUT-737: >>> >> ------------------------------------- >>> >> >>> >> I think so. When will you be releasing 0.6? I am planning to do a bit >>> more extensive testing in the next 2-3 weeks. >>> >> >>> >>> Implicit Alternating Least Squares SVD >>> >>> -------------------------------------- >>> >>> >>> >>> Key: MAHOUT-737 >>> >>> URL: https://issues.apache.org/jira/browse/MAHOUT-737 >>> >>> Project: Mahout >>> >>> Issue Type: New Feature >>> >>> Components: Collaborative Filtering >>> >>> Affects Versions: 0.6 >>> >>> Reporter: Tamas Jambor >>> >>> Assignee: Sebastian Schelter >>> >>> Attachments: MAHOUT-737-2.patch, MAHOUT-737.patch, >>> MAHOUT-737.patch, MAHOUT-737.patch, MAHOUT-737.patch >>> >>> >>> >>> >>> >>> I am sharing this Java implementation of mine that is based on the >>> paper - Collaborative Filtering with Implicit Datasets. The implementation >>> is multi-treading and can be easily extended to use it on Hadoop. In fact >>> this approach would possibly work with non-implicit datasets, but further >>> testing is needed. The algorithm is tried and tested on an implicit >>> TV-viewing dataset, and the performance was pretty good (details to follow). >>> >> >>> >> -- >>> >> This message is automatically generated by JIRA. >>> >> If you think it was sent incorrectly, please contact your JIRA >>> administrators: >>> https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa >>> >> For more information on JIRA, see: >>> http://www.atlassian.com/software/jira >>> >> >>> >> >>> > >>> > >>> > >>> >>>
