Travelled to:1 × China
3 × USA
Collaborated with:P.Valiant A.T.Kalai A.Moitra G.Gottlob S.T.Lee A.Andoni R.Panigrahy L.Zhang A.Agarwal S.M.Kakade N.Karampatziakis L.Song
Talks about:learn (2) estim (2) size (2) treewidth (1) polynomi (1) gaussian (1) conjunct (1) approach (1) support (1) scalabl (1)
Person: Gregory Valiant
DBLP: Valiant:Gregory
Contributed to:
2014
20112010
2009Wrote 5 papers:
- ICML-c2-2014-AgarwalKKSV #multi #predict #scalability
- Least Squares Revisited: Scalable Approaches for Multi-class Prediction (AA, SMK, NK, LS, GV), pp. 541–549.
- ICML-c2-2014-AndoniPV0 #learning #network
- Learning Polynomials with Neural Networks (AA, RP, GV, LZ), pp. 1908–1916.
- STOC-2011-ValiantV
- Estimating the unseen: an n/log(n)-sample estimator for entropy and support size, shown optimal via new CLTs (GV, PV), pp. 685–694.
- STOC-2010-KalaiMV #learning
- Efficiently learning mixtures of two Gaussians (ATK, AM, GV), pp. 553–562.
- PODS-2009-GottlobLV #bound #query
- Size and treewidth bounds for conjunctive queries (GG, STL, GV), pp. 45–54.