Multi-view clustering via canonical correlation analysis K Chaudhuri, SM Kakade, K Livescu, K Sridharan Proceedings of the 26th annual international conference on machine learning …, 2009 | 857 | 2009 |
Making gradient descent optimal for strongly convex stochastic optimization A Rakhlin, O Shamir, K Sridharan arXiv preprint arXiv:1109.5647, 2011 | 666 | 2011 |
Learnability, stability and uniform convergence S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan The Journal of Machine Learning Research 11, 2635-2670, 2010 | 432 | 2010 |
On the complexity of linear prediction: Risk bounds, margin bounds, and regularization SM Kakade, K Sridharan, A Tewari Advances in neural information processing systems 21, 2008 | 363 | 2008 |
Better mini-batch algorithms via accelerated gradient methods A Cotter, O Shamir, N Srebro, K Sridharan Advances in neural information processing systems 24, 2011 | 346 | 2011 |
Stochastic Convex Optimization. S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan COLT 2 (4), 5, 2009 | 312 | 2009 |
Optimization, learning, and games with predictable sequences S Rakhlin, K Sridharan Advances in Neural Information Processing Systems 26, 2013 | 300 | 2013 |
Smoothness, low noise and fast rates N Srebro, K Sridharan, A Tewari Advances in neural information processing systems 23, 2010 | 290* | 2010 |
Online learning with predictable sequences A Rakhlin, K Sridharan Conference on Learning Theory, 993-1019, 2013 | 276 | 2013 |
Online optimization: Competing with dynamic comparators A Jadbabaie, A Rakhlin, S Shahrampour, K Sridharan Artificial Intelligence and Statistics, 398-406, 2015 | 230 | 2015 |
Fast rates for regularized objectives K Sridharan, S Shalev-Shwartz, N Srebro Advances in neural information processing systems 21, 2008 | 161 | 2008 |
On the universality of online mirror descent N Srebro, K Sridharan, A Tewari Advances in neural information processing systems 24, 2011 | 135 | 2011 |
Online learning: Random averages, combinatorial parameters, and learnability A Rakhlin, K Sridharan, A Tewari Advances in Neural Information Processing Systems 23, 2010 | 123 | 2010 |
An information theoretic framework for multi-view learning K Sridharan, SM Kakade | 106 | 2008 |
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals. A Cotter, H Jiang, MR Gupta, S Wang, T Narayan, S You, K Sridharan J. Mach. Learn. Res. 20 (172), 1-59, 2019 | 104 | 2019 |
Selective sampling and active learning from single and multiple teachers O Dekel, C Gentile, K Sridharan The Journal of Machine Learning Research 13 (1), 2655-2697, 2012 | 104 | 2012 |
Sequential complexities and uniform martingale laws of large numbers A Rakhlin, K Sridharan, A Tewari Probability theory and related fields 161, 111-153, 2015 | 102 | 2015 |
Two-player games for efficient non-convex constrained optimization A Cotter, H Jiang, K Sridharan Algorithmic Learning Theory, 300-332, 2019 | 100 | 2019 |
Learning in games: Robustness of fast convergence DJ Foster, Z Li, T Lykouris, K Sridharan, E Tardos Advances in Neural Information Processing Systems 29, 2016 | 94 | 2016 |
Learning kernel-based halfspaces with the 0-1 loss S Shalev-Shwartz, O Shamir, K Sridharan SIAM Journal on Computing 40 (6), 1623-1646, 2011 | 91* | 2011 |