Shai Shalev-Shwartz

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Amnon ShashuaProfessor of Computer Science, the Hebrew University of JerusalemVerified email at cs.huji.ac.il
Ohad ShamirWeizmann Institute of ScienceVerified email at weizmann.ac.il
Nathan SrebroProfessor, TTIC and University of ChicagoVerified email at ttic.edu
Shai Ben-DavidUniverity of Waterloo, CanadaVerified email at uwaterloo.ca
Ofer DekelMicrosoft ResearchVerified email at microsoft.com
Amit DanielyHebrew UniversityVerified email at mail.huji.ac.il
Tong ZhangUIUCVerified email at tongzhang-ml.org
Joseph KeshetProfessor, Faculty of Electrical & Computer Engineering, TechnionVerified email at technion.ac.il
Karthik SridharanCornell University, University of Pennsylvania, Toyota Technological InstituteVerified email at ttic.edu
Ambuj Tewari | अम्बुज तिवारीProfessor, Statistics and EECS, University of MichiganVerified email at umich.edu
Roi LivniTel Aviv UniversityVerified email at tauex.tau.ac.il
John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford UniversityVerified email at stanford.edu
Sivan SabatoMcMaster University; Canada CIFAR AI Chair, Vector InstituteVerified email at mcmaster.ca
Sham M KakadeHarvard UniversityVerified email at seas.harvard.edu
Amir GlobersonTel Aviv UniversityVerified email at post.tau.ac.il
Tushar ChandraGoogleVerified email at google.com
Nicolò Cesa-BianchiProfessor of Computer Science, Università degli Studi di Milano and Politecnico di MilanoVerified email at unimi.it
Elad HazanProfessor at Princeton University and Director Google AI PrincetonVerified email at princeton.edu
Kfir Yehuda LevyAssistant Professor at Technion - Israel Institute of TechnologyVerified email at technion.ac.il
Nati LinialProfessor of Computer Science, The Hebrew University of JerusalemVerified email at cs.huji.ac.il

Shai Shalev-Shwartz

The Hebrew University

Verified email at cs.huji.ac.il - Homepage

Machine Learning Learning Theory Online Learning Self-driving Cars


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Understanding Machine Learning: From Theory to Algorithms S Shalev-Shwartz, S Ben-David Cambridge University Press, 2014	8463	2014
Understanding Machine Learning: From Theory to Algorithms S Shalev-Shwartz, S Ben-David Cambridge University Press, 2014	8463	2014
Pegasos: Primal estimated sub-gradient solver for svm S Shalev-Shwartz, Y Singer, N Srebro Proceedings of the 24th international conference on Machine learning, 807-814, 2007	2893	2007
Online passive-aggressive algorithms. K Crammer, O Dekel, J Keshet, S Shalev-Shwartz, Y Singer, MK Warmuth Journal of Machine Learning Research 7 (3), 2006	2643	2006
Online learning and online convex optimization S Shalev-Shwartz Foundations and Trends® in Machine Learning 4 (2), 107-194, 2012	2599	2012
Efficient projections onto the l₁-ball for learning in high dimensions J Duchi, S Shalev-Shwartz, Y Singer, T Chandra Proceedings of the 25th international conference on Machine learning, 272-279, 2008	1746	2008
Stochastic dual coordinate ascent methods for regularized loss minimization. S Shalev-Shwartz, T Zhang Journal of Machine Learning Research 14 (1), 2013	1238	2013
Safe, multi-agent, reinforcement learning for autonomous driving S Shalev-Shwartz, S Shammah, A Shashua arXiv preprint arXiv:1610.03295, 2016	1139	2016
On a formal model of safe and scalable self-driving cars S Shalev-Shwartz arXiv preprint arXiv:1708.06374, 2017	1054	2017
Decoupling" when to update" from" how to update" E Malach, S Shalev-Shwartz Advances in neural information processing systems 30, 2017	663	2017
On the computational efficiency of training neural networks R Livni, S Shalev-Shwartz, O Shamir Advances in neural information processing systems 27, 2014	627	2014
Learnability, stability and uniform convergence S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan The Journal of Machine Learning Research 11, 2635-2670, 2010	567	2010
Stochastic methods for l₁ regularized loss minimization S Shalev-Shwartz, A Tewari Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	523	2009
Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization S Shalev-Shwartz, T Zhang International conference on machine learning, 64-72, 2014	521	2014
Composite objective mirror descent. JC Duchi, S Shalev-Shwartz, Y Singer, A Tewari Colt 10, 14-26, 2010	422	2010
Online and batch learning of pseudo-metrics S Shalev-Shwartz, Y Singer, AY Ng Proceedings of the twenty-first international conference on Machine learning, 94, 2004	417	2004
Stochastic Convex Optimization. S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan COLT 2 (4), 5, 2009	384	2009
Online learning: Theory, algorithms, and applications S Shalev-Shwartz Hebrew University, 2007	372	2007
SVM optimization: inverse dependence on training set size S Shalev-Shwartz, N Srebro Proceedings of the 25th international conference on Machine learning, 928-935, 2008	340	2008
Proving the lottery ticket hypothesis: Pruning is all you need E Malach, G Yehudai, S Shalev-Schwartz, O Shamir International Conference on Machine Learning, 6682-6691, 2020	310	2020

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