| Contextual bandits with linear payoff functions W Chu, L Li, L Reyzin, RE Schapire International Conference on Artificial Intelligence and Statistics, 2011 | 504 | 2011 |
| How boosting the margin can also boost classifier complexity L Reyzin, RE Schapire International Conference on Machine Learning, 753-760, 2006 | 244 | 2006 |
| Efficient optimal learning for contextual bandits M Dudik, D Hsu, S Kale, N Karampatziakis, J Langford, L Reyzin, T Zhang Conference on Uncertainty in Artificial Intelligence, 2011 | 205 | 2011 |
| Contextual bandit algorithms with supervised learning guarantees A Beygelzimer, J Langford, L Li, L Reyzin, RE Schapire International Conference on Artificial Intelligence and Statistics, 2011 | 178 | 2011 |
| Statistical algorithms and a lower bound for detecting planted cliques V Feldman, E Grigorescu, L Reyzin, SS Vempala, Y Xiao Journal of the ACM 64 (2), 8, 2017 | 167 | 2017 |
| Non-stochastic bandit slate problems S Kale, L Reyzin, RE Schapire Neural Information Processing Systems, 1054-1062, 2010 | 76 | 2010 |
| Network construction with subgraph connectivity constraints D Angluin, J Aspnes, L Reyzin Journal of Combinatorial Optimization 29 (2), 418–432, 2015 | 49* | 2015 |
| Learning and verifying graphs using queries with a focus on edge counting L Reyzin, N Srivastava International Conference on Algorithmic Learning Theory, 285-297, 2007 | 44 | 2007 |
| Data stability in clustering: a closer look S Ben-David, L Reyzin Theoretical Computer Science 558, 51–61, 2014 | 41* | 2014 |
| Boosting on a budget: sampling for feature-efficient prediction L Reyzin International Conference on Machine Learning, 2011 | 30* | 2011 |
| Anti-coordination games and stable graph colorings J Kun, B Powers, L Reyzin Symposium on Algorithmic Game Theory, 122-133, 2013 | 28 | 2013 |
| On the longest path algorithm for reconstructing trees from distance matrices L Reyzin, N Srivastava Information processing letters 101 (3), 98-100, 2007 | 27 | 2007 |
| Shift-pessimistic active learning using robust bias-aware prediction A Liu, L Reyzin, BD Ziebart Conference on Artificial Intelligence, 2015 | 23* | 2015 |
| On the computational complexity of MapReduce B Fish, J Kun, ÁD Lelkes, L Reyzin, G Turán Symposium on Distributed Computing, 2015 | 22 | 2015 |
| On noise-tolerant learning of sparse parities and related problems E Grigorescu, L Reyzin, S Vempala International Conference on Algorithmic Learning Theory, 413-424, 2011 | 19 | 2011 |
| Learning large-alphabet and analog circuits with value injection queries D Angluin, J Aspnes, J Chen, L Reyzin Conference on Learning Theory, 51-65, 2007 | 16 | 2007 |
| Optimally learning social networks with activations and suppressions D Angluin, J Aspnes, L Reyzin Theoretical computer science 411 (29-30), 2729-2740, 2010 | 15 | 2010 |
| Unprovability comes to machine learning L Reyzin Nature 565 (7738), 166-167, 2019 | 14 | 2019 |
| Lower bounds on learning random structures with statistical queries D Angluin, D Eisenstat, AL Kontorovich, L Reyzin International Conference on Algorithmic Learning Theory, 194-208, 2010 | 12 | 2010 |
| On the complexity of learning from label proportions B Fish, L Reyzin International Joint Conference on Artificial Intelligence, 2017 | 11 | 2017 |
Robert SchapireMicrosoft ResearchVerified email at microsoft.com
