On Wed, Apr 1, 2009 at 1:30 AM, Ted Dunning <[email protected]> wrote:
> I would hope that your SVD implementation would not be limited to NetFlix > like problems, but would be applicable to any reasonably sparse matrix-like > data. > Yes, ofcourse. it would apply to any large sparse matrix implementation. > > Likewise, I would expect a good SVD implementation to be useful for nearest > neighbor methods or direct prediction by smoothing the history vector. > I do not have knowledge about this as of now, will read up and comment. > > On Tue, Mar 31, 2009 at 11:09 PM, Atul Kulkarni <[email protected] > >wrote: > > > I have worked with Netflix Prize problem and hence most of my suggested > > algorithms revolve around that problem. But I am open to other algorithms > > that might be out there. Is this a good thing to do? > > > > > > -- > Ted Dunning, CTO > DeepDyve > -- Regards, Atul Kulkarni Teaching Assistant, Department of Computer Science, University of Minnesota Duluth Duluth. 55805. www.d.umn.edu/~kulka053
