Travelled to:1 × Canada
1 × Finland
1 × France
1 × Norway
2 × China
4 × USA
Collaborated with:P.Kar I.S.Dhillon H.Narasimhan P.Netrapalli A.G.Thakurta S.Bhojanapalli A.Thakurta S.Sanghavi Z.Lu H.Yu S.Gopi A.V.Nori B.K.Sriperumbudur H.Karnick R.Meka C.Caramanis S.Amer-Yahia I.Fundulaki L.V.S.Lakshmanan P.Hitzler K.Verma P.Z.Yeh A.P.Sheth J.V.Davis B.Kulis S.Sra
Talks about:learn (7) differenti (2) function (2) complet (2) privat (2) metric (2) matrix (2) onlin (2) minim (2) label (2)
Person: Prateek Jain
DBLP: Jain:Prateek
Contributed to:
2015201420142013
2013
2012200920082007
2005Wrote 14 papers:
- ICML-2015-KarN0 #precise
- Surrogate Functions for Maximizing Precision at the Top (PK, HN, PJ), pp. 189–198.
- ICML-2015-NarasimhanK0 #metric #optimisation #performance
- Optimizing Non-decomposable Performance Measures: A Tale of Two Classes (HN, PK, PJ), pp. 199–208.
- ICML-c1-2014-JainT #bound #independence #learning
- (Near) Dimension Independent Risk Bounds for Differentially Private Learning (PJ, AGT), pp. 476–484.
- ICML-c1-2014-Yu0KD #learning #multi #scalability
- Large-scale Multi-label Learning with Missing Labels (HFY, PJ, PK, ISD), pp. 593–601.
- ICML-c2-2014-Bhojanapalli0 #matrix
- Universal Matrix Completion (SB, PJ), pp. 1881–1889.
- ICML-c3-2013-0002T #kernel #learning
- Differentially Private Learning with Kernels (PJ, AT), pp. 118–126.
- ICML-c3-2013-GopiN0N
- One-Bit Compressed Sensing: Provable Support and Vector Recovery (SG, PN, PJ, AVN), pp. 154–162.
- ICML-c3-2013-KarS0K #algorithm #learning #on the #online
- On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions (PK, BKS, PJ, HK), pp. 441–449.
- STOC-2013-JainNS #matrix #rank #using
- Low-rank matrix completion using alternating minimization (PJ, PN, SS), pp. 665–674.
- HT-2012-JainHVYS #detection #linked data #open data
- Moving beyond SameAs with PLATO: partonomy detection for linked data (PJ, PH, KV, PZY, APS), pp. 33–42.
- ICML-2009-LuJD #geometry #learning #metric
- Geometry-aware metric learning (ZL, PJ, ISD), pp. 673–680.
- ICML-2008-MekaJCD #learning #online #rank
- Rank minimization via online learning (RM, PJ, CC, ISD), pp. 656–663.
- ICML-2007-DavisKJSD #learning #metric
- Information-theoretic metric learning (JVD, BK, PJ, SS, ISD), pp. 209–216.
- VLDB-2005-Amer-YahiaFJL #personalisation #xml
- Personalizing XML Text Search in PimenT (SAY, IF, PJ, LVSL), pp. 1310–1313.