Travelled to:1 × Australia
1 × China
1 × Finland
1 × Israel
1 × United Kingdom
3 × Canada
4 × USA
Collaborated with:A.J.Smola M.N.Murty C.H.Teo M.Varma P.Yanardag M.K.Warmuth N.N.Schraudolph L.Cheng A.Jain S.Matsushima X.Zhang D.Aberdeen V.S.Denchev N.Ding H.Neven B.Hariharan L.Zelnik-Manor J.Yu S.Günter Q.V.Le M.W.Schmidt K.P.Murphy H.Yun H.Yu C.Hsieh I.S.Dhillon W.Benjamin S.K.Chandrasegaran D.Ramanujan N.Elmqvist K.Ramani
Talks about:kernel (4) optim (3) multi (3) learn (3) svm (3) algorithm (2) stochast (2) support (2) classif (2) random (2)
Person: S. V. N. Vishwanathan
DBLP: Vishwanathan:S=_V=_N=
Contributed to:
2015
2014
2014
201220122010200920082007200720062003
2002Wrote 16 papers:
- KDD-2015-YanardagV #graph #kernel
- Deep Graph Kernels (PY, SVNV), pp. 1365–1374.
- CHI-2014-BenjaminCREVR #composition #named
- Juxtapoze: supporting serendipity and creative expression in clipart compositions (WB, SKC, DR, NE, SVNV, KR), pp. 341–350.
- VLDB-2014-YunYHVD #algorithm #distributed #matrix #multi #named #probability
- NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion (HY, HFY, CJH, SVNV, ISD), pp. 975–986.
- ICML-2012-DenchevDVN #classification #optimisation #quantum #robust
- Robust Classification with Adiabatic Quantum Optimization (VSD, ND, SVNV, HN), p. 131.
- KDD-2012-JainVV #kernel #learning #multi #named
- SPF-GMKL: generalized multiple kernel learning with a million kernels (AJ, SVNV, MV), pp. 750–758.
- KDD-2012-MatsushimaVS #linear
- Linear support vector machines via dual cached loops (SM, SVNV, AJS), pp. 177–185.
- ICML-2010-HariharanZVV #classification #multi #scalability
- Large Scale Max-Margin Multi-Label Classification with Priors (BH, LZM, SVNV, MV), pp. 423–430.
- ICML-2009-WarmuthV #optimisation #overview #perspective #summary #tutorial
- Tutorial summary: Survey of boosting from an optimization perspective (MKW, SVNV), p. 15.
- ICML-2008-YuVGS #approach #optimisation
- A quasi-Newton approach to non-smooth convex optimization (JY, SVNV, SG, NNS), pp. 1216–1223.
- ICML-2007-ChengV #image #learning
- Learning to compress images and videos (LC, SVNV), pp. 161–168.
- ICML-2007-ZhangAV #learning #multi #random
- Conditional random fields for multi-agent reinforcement learning (XZ, DA, SVNV), pp. 1143–1150.
- KDD-2007-TeoSVL #composition #scalability
- A scalable modular convex solver for regularized risk minimization (CHT, AJS, SVNV, QVL), pp. 727–736.
- ICML-2006-TeoV #array #kernel #performance #string #using
- Fast and space efficient string kernels using suffix arrays (CHT, SVNV), pp. 929–936.
- ICML-2006-VishwanathanSSM #probability #random
- Accelerated training of conditional random fields with stochastic gradient methods (SVNV, NNS, MWS, KPM), pp. 969–976.
- ICML-2003-VishwanathanSM
- SimpleSVM (SVNV, AJS, MNM), pp. 760–767.
- ICPR-v2-2002-VishwanathanM #algorithm #geometry #performance
- Geometric SVM: A Fast and Intuitive SVM Algorithm (SVNV, MNM), pp. 56–59.