| A global geometric framework for nonlinear dimensionality reduction JB Tenenbaum, V Silva, JC Langford science 290 (5500), 2319-2323, 2000 | 17232 | 2000 |
| A contextual-bandit approach to personalized news article recommendation L Li, W Chu, J Langford, RE Schapire Proceedings of the 19th international conference on World wide web, 661-670, 2010 | 3533 | 2010 |
| CAPTCHA: Using hard AI problems for security L Von Ahn, M Blum, NJ Hopper, J Langford Advances in Cryptology—EUROCRYPT 2003: International Conference on the …, 2003 | 2223 | 2003 |
| Doubly robust policy evaluation and learning M Dudík, J Langford, L Li arXiv preprint arXiv:1103.4601, 2011 | 1288* | 2011 |
| A reductions approach to fair classification A Agarwal, A Beygelzimer, M Dudík, J Langford, H Wallach International conference on machine learning, 60-69, 2018 | 1282 | 2018 |
| Approximately optimal approximate reinforcement learning S Kakade, J Langford Proceedings of the Nineteenth International Conference on Machine Learning …, 2002 | 1277 | 2002 |
| Telling humans and computers apart automatically L Von Ahn, M Blum, J Langford Communications of the ACM 47 (2), 56-60, 2004 | 1272 | 2004 |
| Feature hashing for large scale multitask learning K Weinberger, A Dasgupta, J Langford, A Smola, J Attenberg Proceedings of the 26th annual international conference on machine learning …, 2009 | 1222 | 2009 |
| Cover trees for nearest neighbor A Beygelzimer, S Kakade, J Langford Proceedings of the 23rd international conference on Machine learning, 97-104, 2006 | 1163 | 2006 |
| Cost-sensitive learning by cost-proportionate example weighting B Zadrozny, J Langford, N Abe Third IEEE international conference on data mining, 435-442, 2003 | 922 | 2003 |
| Deep batch active learning by diverse, uncertain gradient lower bounds JT Ash, C Zhang, A Krishnamurthy, J Langford, A Agarwal arXiv preprint arXiv:1906.03671, 2019 | 821 | 2019 |
| The epoch-greedy algorithm for multi-armed bandits with side information J Langford, T Zhang Advances in neural information processing systems 20, 2007 | 765 | 2007 |
| Search-based structured prediction H Daumé, J Langford, D Marcu Machine learning 75, 297-325, 2009 | 714 | 2009 |
| Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms L Li, W Chu, J Langford, X Wang Proceedings of the fourth ACM international conference on Web search and …, 2011 | 690 | 2011 |
| Scaling up machine learning: Parallel and distributed approaches R Bekkerman, M Bilenko, J Langford Cambridge University Press, 2011 | 677 | 2011 |
| PAC model-free reinforcement learning AL Strehl, L Li, E Wiewiora, J Langford, ML Littman Proceedings of the 23rd international conference on Machine learning, 881-888, 2006 | 654 | 2006 |
| Agnostic active learning MF Balcan, A Beygelzimer, J Langford Proceedings of the 23rd international conference on Machine learning, 65-72, 2006 | 640 | 2006 |
| 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 | 592 | 2014 |
| Sparse Online Learning via Truncated Gradient. J Langford, L Li, T Zhang Journal of Machine Learning Research 10 (3), 2009 | 566 | 2009 |
| Multi-label prediction via compressed sensing DJ Hsu, SM Kakade, J Langford, T Zhang Advances in neural information processing systems 22, 2009 | 531 | 2009 |
