| Pegasos: Primal estimated sub-gradient solver for svm S Shalev-Shwartz, Y Singer, N Srebro, A Cotter Mathematical programming 127 (1), 3-30, 2011 | 2356 | 2011 |
| Equality of opportunity in supervised learning M Hardt, E Price, N Srebro Advances in neural information processing systems, 3315-3323, 2016 | 1295 | 2016 |
| Maximum-margin matrix factorization N Srebro, J Rennie, T Jaakkola Advances in neural information processing systems 17, 1329-1336, 2004 | 1192 | 2004 |
| Fast maximum margin matrix factorization for collaborative prediction JDM Rennie, N Srebro Proceedings of the 22nd international conference on Machine learning, 713-719, 2005 | 1129 | 2005 |
| Weighted low-rank approximations N Srebro, T Jaakkola Proceedings of the 20th International Conference on Machine Learning (ICML …, 2003 | 865 | 2003 |
| The marginal value of adaptive gradient methods in machine learning AC Wilson, R Roelofs, M Stern, N Srebro, B Recht Advances in neural information processing systems, 4148-4158, 2017 | 596 | 2017 |
| Exploring generalization in deep learning B Neyshabur, S Bhojanapalli, D McAllester, N Srebro Advances in neural information processing systems, 5947-5956, 2017 | 476 | 2017 |
| Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm D Needell, N Srebro, R Ward Mathematical Programming 155 (1-2), 549-573, 2016 | 401 | 2016 |
| Rank, trace-norm and max-norm N Srebro, A Shraibman International Conference on Computational Learning Theory, 545-560, 2005 | 382 | 2005 |
| Uncovering shared structures in multiclass classification Y Amit, M Fink, N Srebro, S Ullman Proceedings of the 24th international conference on Machine learning, 17-24, 2007 | 359 | 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 | 304 | 2008 |
| The implicit bias of gradient descent on separable data D Soudry, E Hoffer, MS Nacson, S Gunasekar, N Srebro The Journal of Machine Learning Research 19 (1), 2822-2878, 2018 | 295 | 2018 |
| Communication-efficient distributed optimization using an approximate newton-type method O Shamir, N Srebro, T Zhang International conference on machine learning, 1000-1008, 2014 | 294 | 2014 |
| Global optimality of local search for low rank matrix recovery S Bhojanapalli, B Neyshabur, N Srebro Advances in Neural Information Processing Systems, 3873-3881, 2016 | 287 | 2016 |
| Norm-based capacity control in neural networks B Neyshabur, R Tomioka, N Srebro Conference on Learning Theory, 1376-1401, 2015 | 287 | 2015 |
| Learnability, stability and uniform convergence S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan The Journal of Machine Learning Research 11, 2635-2670, 2010 | 287 | 2010 |
| Better mini-batch algorithms via accelerated gradient methods A Cotter, O Shamir, N Srebro, K Sridharan Advances in neural information processing systems, 1647-1655, 2011 | 268 | 2011 |
| A pac-bayesian approach to spectrally-normalized margin bounds for neural networks B Neyshabur, S Bhojanapalli, N Srebro arXiv preprint arXiv:1707.09564, 2017 | 262 | 2017 |
| In search of the real inductive bias: On the role of implicit regularization in deep learning B Neyshabur, R Tomioka, N Srebro arXiv preprint arXiv:1412.6614, 2014 | 239 | 2014 |
| Stochastic Convex Optimization. S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan COLT, 2009 | 239 | 2009 |
Shai Shalev-ShwartzThe Hebrew UniversityAdresse e-mail validée de cs.huji.ac.il
