Travelled to:1 × Finland
1 × France
1 × USA
Collaborated with:N.Satish P.Dubey M.M.A.Patwary B.C.Catanzaro K.Keutzer S.Madden R.Taft M.Vartak N.R.Satish M.Stonebraker A.Turmukhametova T.Mostak P.Indyk S.Dulloor M.J.Anderson S.G.Vadlamudi D.Das J.Snoek O.Rippel K.Swersky R.Kiros Prabhat R.P.Adams J.Seo J.Park M.A.Hassaan S.Sengupta Z.Yin
Talks about:graph (4) analyt (3) use (3) processor (1) framework (1) benchmark (1) parallel (1) bayesian (1) support (1) similar (1)
Person: Narayanan Sundaram
DBLP: Sundaram:Narayanan
Contributed to:
2015
2015
201420132008Wrote 6 papers:
- ICML-2015-SnoekRSKSSPPA #network #optimisation #scalability #using
- Scalable Bayesian Optimization Using Deep Neural Networks (JS, OR, KS, RK, NS, NS, MMAP, P, RPA), pp. 2171–2180.
- VLDB-2015-SundaramSPDAV0D #effectiveness #graph #named #performance
- GraphMat: High performance graph analytics made productive (NS, NS, MMAP, SD, MJA, SGV, DD, PD), pp. 1214–1225.
- SIGMOD-2014-SatishSPSPHSYD #dataset #framework #graph #navigation #using
- Navigating the maze of graph analytics frameworks using massive graph datasets (NS, NS, MMAP, JS, JP, MAH, SS, ZY, PD), pp. 979–990.
- SIGMOD-2014-TaftVSSMS #benchmark #metric #named
- GenBase: a complex analytics genomics benchmark (RT, MV, NRS, NS, SM, MS), pp. 177–188.
- VLDB-2013-SundaramTSMIMD #parallel #similarity #streaming #twitter #using
- Streaming Similarity Search over one Billion Tweets using Parallel Locality-Sensitive Hashing (NS, AT, NS, TM, PI, SM, PD), pp. 1930–1941.
- ICML-2008-CatanzaroSK #classification #performance
- Fast support vector machine training and classification on graphics processors (BCC, NS, KK), pp. 104–111.