BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
Travelled to:
1 × France
1 × Israel
1 × United Kingdom
2 × Canada
2 × China
2 × Finland
5 × USA
Collaborated with:
Y.Singer N.Srebro A.Gonen A.Tewari A.Daniely A.Cotter O.Shamir T.Zhang A.Vinnikov A.Globerson N.Linial N.Srebro S.Sabato R.Urner S.Ben-David N.Cesa-Bianchi S.M.Kakade A.Y.Ng E.Eban A.Birnbaum J.C.Duchi T.Chandra M.Fink S.Ullman S.Dubnov N.Friedman R.Livni D.Lehavi S.Schein H.Nachlieli
Talks about:
learn (9) onlin (5) effici (4) stochast (3) predict (3) minim (3) multiclass (2) regular (2) complex (2) compon (2)

Person: Shai Shalev-Shwartz

DBLP DBLP: Shalev-Shwartz:Shai

Contributed to:

ICML 20152015
ICML c1 20142014
ICML c2 20142014
STOC 20142014
ICML c1 20132013
ICML 20122012
ICML 20112011
ICML 20102010
ICML 20092009
ICML 20082008
ICML 20072007
ICML 20062006
ICML 20042004
SIGIR 20022002

Wrote 20 papers:

ICML-2015-DanielyGS #adaptation #learning #online
Strongly Adaptive Online Learning (AD, AG, SSS), pp. 1405–1411.
ICML-c1-2014-Shalev-Shwartz0 #coordination #probability
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization (SSS, TZ), pp. 64–72.
ICML-c2-2014-VinnikovS #component #independence
K-means recovers ICA filters when independent components are sparse (AV, SSS), pp. 712–720.
STOC-2014-DanielyLS #complexity #learning
From average case complexity to improper learning complexity (AD, NL, SSS), pp. 441–448.
ICML-c1-2013-CotterSS #learning
Learning Optimally Sparse Support Vector Machines (AC, SSS, NS), pp. 266–274.
ICML-c1-2013-GonenSS #approach #learning #performance
Efficient Active Learning of Halfspaces: an Aggressive Approach (AG, SS, SSS), pp. 480–488.
ICML-c1-2013-LivniLSNSG #analysis #component
Vanishing Component Analysis (RL, DL, SS, HN, SSS, AG), pp. 597–605.
ICML-2012-CotterSS #kernel #probability
The Kernelized Stochastic Batch Perceptron (AC, SSS, NS), p. 98.
ICML-2012-EbanBSG #learning #online #predict #sequence
Learning the Experts for Online Sequence Prediction (EE, AB, SSS, AG), p. 38.
ICML-2011-Shalev-ShwartzGS #constraints #rank #scalability
Large-Scale Convex Minimization with a Low-Rank Constraint (SSS, AG, OS), pp. 329–336.
ICML-2011-UrnerSB #predict
Access to Unlabeled Data can Speed up Prediction Time (RU, SSS, SBD), pp. 641–648.
ICML-2010-Cesa-BianchiSS #learning #performance
Efficient Learning with Partially Observed Attributes (NCB, SSS, OS), pp. 183–190.
ICML-2009-Shalev-ShwartzT #probability
Stochastic methods for l1 regularized loss minimization (SSS, AT), pp. 929–936.
ICML-2008-DuchiSSC #learning #performance
Efficient projections onto the l1-ball for learning in high dimensions (JCD, SSS, YS, TC), pp. 272–279.
ICML-2008-KakadeST #algorithm #multi #online #performance #predict
Efficient bandit algorithms for online multiclass prediction (SMK, SSS, AT), pp. 440–447.
ICML-2008-Shalev-ShwartzS #dependence #optimisation #set
SVM optimization: inverse dependence on training set size (SSS, NS), pp. 928–935.
ICML-2007-Shalev-ShwartzSS #named
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM (SSS, YS, NS), pp. 807–814.
ICML-2006-FinkSSU #learning #multi #online
Online multiclass learning by interclass hypothesis sharing (MF, SSS, YS, SU), pp. 313–320.
ICML-2004-Shalev-ShwartzSN #learning #online #pseudo
Online and batch learning of pseudo-metrics (SSS, YS, AYN).
SIGIR-2002-Shalev-ShwartzDFS #modelling #query #robust
Robust temporal and spectral modeling for query By melody (SSS, SD, NF, YS), pp. 331–338.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.