On Thu, Sep 21, 2017 at 3:51 PM, Zhang, Hong <[email protected]> wrote:
> Great news! According to their papers, MLSVM works only in serial. I am > not sure what is stopping them using PETSc in parallel. > I think its because they use FLANN (http://www.cs.ubc.ca/research/flann/) which appears to be serial. Richard, it looks like your parallel clustering could get you another few papers :) Matt > Btw, are there any other cases that use PETSc for machine learning? > > Hong (Mr.) > > > On Sep 21, 2017, at 1:02 PM, Barry Smith <[email protected]> wrote: > > > > > > From: Ilya Safro [email protected] > > Date: September 17, 2017 > > Subject: MLSVM 1.0, Multilevel Support Vector Machines > > > > We are pleased to announce the release of MLSVM 1.0, a library of fast > > multilevel algorithms for training nonlinear support vector machine > > models on large-scale datasets. The library is developed as an > > extension of PETSc to support, among other applications, the analysis > > of datasets in scientific computing. > > > > Highlights: > > - The best quality/performance trade-off is achieved with algebraic > > multigrid coarsening > > - Tested on academic, industrial, and healthcare datasets > > - Generates multiple models for each training > > - Effective on imbalanced datasets > > > > Download MLSVM at https://github.com/esadr/mlsvm > > > > Corresponding paper: Sadrfaridpour, Razzaghi and Safro "Engineering > > multilevel support vector machines", 2017, > > https://arxiv.org/pdf/1707.07657.pdf > > > > -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener http://www.caam.rice.edu/~mk51/
