Okay, I see the point now. Let me dig a bit deeper and I will get back soon. Thanks for the comments.
-- Aditya Sarawgi On Thu, Mar 1, 2012 at 2:06 AM, Ted Dunning <[email protected]> wrote: > No. By linear SVM, I mean SVM that does not use the kernel trick. > > This is like logistic regression SGD with a different gradient function. > Same idea otherwise. Yes. This is a convex problem. > > > On Wed, Feb 29, 2012 at 10:50 PM, Aditya Sarawgi <[email protected] > > wrote: > >> So if I understand correctly, I think you mean that instead of having >> multiple layers of svm >> I just have 1 layer that gets the svm of the individual datasets and in >> the reducer I get the >> optimal of all. But is it guaranteed to give a global optima ? >> >> On Thu, Mar 1, 2012 at 1:37 AM, Ted Dunning <[email protected]>wrote: >> >>> For linear SVM, gradient descent is a fine algorithm. If you go into >>> this >>> work, I would recommend that you implement an all-reduce operation since >>> iterated map-reduce is very inefficient. >>> >>> On Wed, Feb 29, 2012 at 10:30 PM, Aditya Sarawgi >>> <[email protected]>wrote: >>> >>> > Hi, >>> > >>> > Thanks Todd for the pointer. I actually had one more paper in mind, >>> and its >>> > from >>> > the original author of SVM >>> > http://leon.bottou.org/publications/pdf/nips-2004c.pdf >>> > >>> > I think this makes more sense for mapreduce. I am open to other >>> suggestions >>> > or >>> > algorithms. >>> > >>> > Thanks >>> > Aditya Sarawgi >>> > >>> > On Thu, Mar 1, 2012 at 1:04 AM, Todd Johnson <[email protected]> >>> > wrote: >>> > >>> > > The authors of that paper don't believe their algorithm is a good >>> > candidate >>> > > for mapreduce. See: >>> > > >>> > >>> http://groups.google.com/group/psvm/browse_thread/thread/cedd3a6caef0f9c9# >>> > > >>> > > todd. >>> > > >>> > > >>> > > >>> > > On Wed, Feb 29, 2012 at 9:31 PM, Aditya Sarawgi < >>> > [email protected] >>> > > >wrote: >>> > > >>> > > > Hello, >>> > > > >>> > > > I am looking to implement psvm for Mahout as a part of of my >>> > coursework. >>> > > > The reference paper is >>> > > > http://books.nips.cc/papers/files/nips20/NIPS2007_0435.pdf >>> > > > and there is a implementation over >>> http://code.google.com/p/psvm/which >>> > > > uses MPI. >>> > > > Any ideas, pointers are much appreciated. >>> > > > >>> > > > Thanks >>> > > > Aditya Sarawgi >>> > > > >>> > > >>> > >>> > >>> > >>> > -- >>> > Cheers, >>> > Aditya Sarawgi >>> > >>> >> >> >> >> -- >> Cheers, >> Aditya Sarawgi >> > >
