| Dual averaging for distributed optimization: Convergence analysis and network scaling JC Duchi, A Agarwal, MJ Wainwright IEEE Transactions on Automatic control 57 (3), 592-606, 2011 | 982 | 2011 |
| Distributed delayed stochastic optimization A Agarwal, JC Duchi Advances in neural information processing systems, 873-881, 2011 | 507 | 2011 |
| A reliable effective terascale linear learning system A Agarwal, O Chapelle, M Dudík, J Langford The Journal of Machine Learning Research 15 (1), 1111-1133, 2014 | 373 | 2014 |
| Fast global convergence rates of gradient methods for high-dimensional statistical recovery A Agarwal, S Negahban, MJ Wainwright Advances in Neural Information Processing Systems, 37-45, 2010 | 335 | 2010 |
| Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization A Agarwal, PL Bartlett, P Ravikumar, MJ Wainwright IEEE Transactions on Information Theory 58 (5), 3235-3249, 2012 | 324 | 2012 |
| A reductions approach to fair classification A Agarwal, A Beygelzimer, M Dudík, J Langford, H Wallach arXiv preprint arXiv:1803.02453, 2018 | 308 | 2018 |
| Taming the monster: A fast and simple algorithm for contextual bandits A Agarwal, D Hsu, S Kale, J Langford, L Li, R Schapire International Conference on Machine Learning, 1638-1646, 2014 | 296 | 2014 |
| Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions A Agarwal, S Negahban, MJ Wainwright The Annals of Statistics 40 (2), 1171-1197, 2012 | 248 | 2012 |
| Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback. A Agarwal, O Dekel, L Xiao COLT, 28-40, 2010 | 240 | 2010 |
| Learning to search better than your teacher KW Chang, A Krishnamurthy, A Agarwal, H Daume, J Langford International Conference on Machine Learning, 2058-2066, 2015 | 163 | 2015 |
| Learning sparsely used overcomplete dictionaries via alternating minimization A Agarwal, A Anandkumar, P Jain, P Netrapalli SIAM Journal on Optimization 26 (4), 2775-2799, 2016 | 154 | 2016 |
| Learning to rank networked entities A Agarwal, S Chakrabarti, S Aggarwal Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006 | 134 | 2006 |
| Stochastic convex optimization with bandit feedback A Agarwal, DP Foster, D Hsu, SM Kakade, A Rakhlin SIAM Journal on Optimization 23 (1), 213-240, 2013 | 126 | 2013 |
| A lower bound for the optimization of finite sums A Agarwal, L Bottou International conference on machine learning, 78-86, 2015 | 119 | 2015 |
| Contextual decision processes with low bellman rank are pac-learnable N Jiang, A Krishnamurthy, A Agarwal, J Langford, RE Schapire International Conference on Machine Learning, 1704-1713, 2017 | 118 | 2017 |
| Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes. P Ravikumar, A Agarwal, MJ Wainwright Journal of Machine Learning Research 11 (3), 2010 | 117 | 2010 |
| Learning sparsely used overcomplete dictionaries A Agarwal, A Anandkumar, P Jain, P Netrapalli, R Tandon Conference on Learning Theory, 123-137, 2014 | 106 | 2014 |
| Fast convergence of regularized learning in games V Syrgkanis, A Agarwal, H Luo, RE Schapire Advances in Neural Information Processing Systems 28, 2989-2997, 2015 | 99 | 2015 |
| A stochastic view of optimal regret through minimax duality J Abernethy, A Agarwal, PL Bartlett, A Rakhlin arXiv preprint arXiv:0903.5328, 2009 | 97 | 2009 |
| Optimality and approximation with policy gradient methods in markov decision processes A Agarwal, SM Kakade, JD Lee, G Mahajan Conference on Learning Theory, 64-66, 2020 | 90 | 2020 |
John LangfordMicrosoft Research New YorkGeverifieerd e-mailadres voor hunch.net
