| A desicion-theoretic generalization of on-line learning and an application to boosting Y Freund, RE Schapire European conference on computational learning theory, 23-37, 1995 | 18620 | 1995 |
| Maximum entropy modeling of species geographic distributions SJ Phillips, RP Anderson, RE Schapire Ecological modelling 190 (3-4), 231-259, 2006 | 11154 | 2006 |
| Experiments with a new boosting algorithm Y Freund, RE Schapire icml 96, 148-156, 1996 | 9499 | 1996 |
| Novel methods improve prediction of species’ distributions from occurrence data J Elith*, C H. Graham*, R P. Anderson, M Dudík, S Ferrier, A Guisan, ... Ecography 29 (2), 129-151, 2006 | 6649 | 2006 |
| The strength of weak learnability RE Schapire Machine learning 5 (2), 197-227, 1990 | 5117 | 1990 |
| Improved boosting algorithms using confidence-rated predictions RE Schapire, Y Singer Machine learning 37 (3), 297-336, 1999 | 4162 | 1999 |
| A short introduction to boosting Y Freund, R Schapire, N Abe Journal-Japanese Society For Artificial Intelligence 14 (771-780), 1612, 1999 | 3509 | 1999 |
| Boosting the margin: A new explanation for the effectiveness of voting methods RE Schapire, Y Freund, P Bartlett, WS Lee The annals of statistics 26 (5), 1651-1686, 1998 | 3141 | 1998 |
| BoosTexter: A boosting-based system for text categorization RE Schapire, Y Singer Machine learning 39 (2-3), 135-168, 2000 | 2659 | 2000 |
| An efficient boosting algorithm for combining preferences Y Freund, R Iyer, RE Schapire, Y Singer Journal of machine learning research 4 (Nov), 933-969, 2003 | 2360 | 2003 |
| Reducing multiclass to binary: A unifying approach for margin classifiers EL Allwein, RE Schapire, Y Singer Journal of machine learning research 1 (Dec), 113-141, 2000 | 2151 | 2000 |
| The boosting approach to machine learning: An overview RE Schapire Nonlinear estimation and classification, 149-171, 2003 | 2026 | 2003 |
| A maximum entropy approach to species distribution modeling SJ Phillips, M Dudík, RE Schapire Proceedings of the twenty-first international conference on Machine learning, 83, 2004 | 1941 | 2004 |
| The nonstochastic multiarmed bandit problem P Auer, N Cesa-Bianchi, Y Freund, RE Schapire SIAM journal on computing 32 (1), 48-77, 2002 | 1659 | 2002 |
| Infogan: Interpretable representation learning by information maximizing generative adversarial nets X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel Advances in neural information processing systems, 2172-2180, 2016 | 1656 | 2016 |
| Large margin classification using the perceptron algorithm Y Freund, RE Schapire Machine learning 37 (3), 277-296, 1999 | 1526 | 1999 |
| A brief introduction to boosting RE Schapire Ijcai 99, 1401-1406, 1999 | 1404 | 1999 |
| 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 | 1353 | 2010 |
| Learning to order things WW Cohen, RE Schapire, Y Singer Advances in neural information processing systems, 451-457, 1998 | 1022 | 1998 |
| How to use expert advice N Cesa-Bianchi, Y Freund, D Haussler, DP Helmbold, RE Schapire, ... Journal of the ACM (JACM) 44 (3), 427-485, 1997 | 803 | 1997 |
