| A global geometric framework for nonlinear dimensionality reduction JB Tenenbaum, V De Silva, JC Langford science 290 (5500), 2319-2323, 2000 | 13131 | 2000 |
| CAPTCHA: Using hard AI problems for security L Von Ahn, M Blum, NJ Hopper, J Langford International Conference on the Theory and Applications of Cryptographic …, 2003 | 1714 | 2003 |
| 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 | 1413 | 2010 |
| Telling humans and computers apart automatically L Von Ahn, M Blum, J Langford Communications of the ACM 47 (2), 56-60, 2004 | 1032 | 2004 |
| Cover trees for nearest neighbor A Beygelzimer, S Kakade, J Langford Proceedings of the 23rd international conference on Machine learning, 97-104, 2006 | 802 | 2006 |
| 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 | 739 | 2009 |
| Cost-sensitive learning by cost-proportionate example weighting B Zadrozny, J Langford, N Abe Third IEEE international conference on data mining, 435-442, 2003 | 636 | 2003 |
| Search-based structured prediction H Daumé, J Langford, D Marcu Machine learning 75 (3), 297-325, 2009 | 486 | 2009 |
| Sparse online learning via truncated gradient J Langford, L Li, T Zhang Journal of Machine Learning Research 10 (Mar), 777-801, 2009 | 449 | 2009 |
| Agnostic active learning MF Balcan, A Beygelzimer, J Langford Journal of Computer and System Sciences 75 (1), 78-89, 2009 | 442 | 2009 |
| Multi-label prediction via compressed sensing DJ Hsu, SM Kakade, J Langford, T Zhang Advances in neural information processing systems, 772-780, 2009 | 414 | 2009 |
| The epoch-greedy algorithm for multi-armed bandits with side information J Langford, T Zhang Advances in neural information processing systems, 817-824, 2008 | 403 | 2008 |
| Scaling up machine learning: Parallel and distributed approaches R Bekkerman, M Bilenko, J Langford Cambridge University Press, 2011 | 375 | 2011 |
| 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 | 355 | 2011 |
| Graph approximations to geodesics on embedded manifolds M Bernstein, V De Silva, JC Langford, JB Tenenbaum Technical report, Department of Psychology, Stanford University, 2000 | 347 | 2000 |
| Approximately optimal approximate reinforcement learning S Kakade, J Langford ICML 2, 267-274, 2002 | 342 | 2002 |
| 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 | 340 | 2006 |
| Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision X Yan, J Yang, E Yumer, Y Guo, H Lee Advances in neural information processing systems, 1696-1704, 2016 | 337* | 2016 |
| 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 | 332 | 2014 |
| Tutorial on practical prediction theory for classification J Langford Journal of machine learning research 6 (Mar), 273-306, 2005 | 321 | 2005 |
