| Tackling the poor assumptions of naive bayes text classifiers JD Rennie, L Shih, J Teevan, D Karger International Conference on Machine Learning 20 (2), 616, 2003 | 1310 | 2003 |
| Maximum-margin matrix factorization N Srebro, J Rennie, TS Jaakkola Advances in neural information processing systems, 1329-1336, 2005 | 1204 | 2005 |
| Fast maximum margin matrix factorization for collaborative prediction JDM Rennie, N Srebro Proceedings of the 22nd international conference on Machine learning, 713-719, 2005 | 1151 | 2005 |
| Automating the construction of internet portals with machine learning AK McCallum, K Nigam, J Rennie, K Seymore Information Retrieval 3 (2), 127-163, 2000 | 830 | 2000 |
| Using reinforcement learning to spider the web efficiently J Rennie, AK McCallum International Conference on Machine Learning, 335-343, 1999 | 381 | 1999 |
| A machine learning approach to building domain-specific search engines A McCallum, K Nigam, J Rennie, K Seymore IJCAI 99, 662-667, 1999 | 269 | 1999 |
| Building Domain-Specific Search Engines with Machine Learning Techniques A McCallum, K Nigam, J Rennie, K Seymore AAAI-99 Spring Symposium, 1999 | 244 | 1999 |
| ifile: An Application of Machine Learning to E-Mail Filtering JDM Rennie KDD-2000 Workshop, 2000 | 218 | 2000 |
| Improving multiclass text classification with the support vector machine JDM Rennie, R Rifkin | 196 | 2001 |
| Topcat: Data mining for topic identification in a text corpus C Clifton, R Cooley, J Rennie IEEE transactions on knowledge and data engineering 16 (8), 949-964, 2004 | 156 | 2004 |
| Improving multi-class text classification with naive Bayes JDM Rennie | 148 | 2001 |
| Loss functions for preference levels: Regression with discrete ordered labels JDM Rennie, N Srebro Proceedings of the IJCAI multidisciplinary workshop on advances in …, 2005 | 135 | 2005 |
| Using term informativeness for named entity detection JDM Rennie, T Jaakkola Proceedings of the 28th annual international ACM SIGIR conference on …, 2005 | 72 | 2005 |
| Statistical analysis of stochastic gradient methods for generalized linear models P Toulis, E Airoldi, J Rennie International Conference on Machine Learning, 667-675, 2014 | 54 | 2014 |
| Text bundling: Statistics based data-reduction L Shih, JD Rennie, YH Chang, DR Karger Proceedings of the 20th International Conference on Machine Learning (ICML …, 2003 | 49 | 2003 |
| Derivation of the F-Measure JDM Rennie other words 1 (4), 2004 | 39 | 2004 |
| Efficient web spidering with reinforcement learning J Rennie, A McCallum Proceedings of the International Conference on Machine Learning, 1999 | 30 | 1999 |
| Regularized logistic regression is strictly convex JDM Rennie Unpublished manuscript. URL people. csail. mit. edu/jrennie/writing/convexLR …, 2005 | 27 | 2005 |
| Another sys called Qanda E Breck, J Burger, L Ferro, W Greiff, M Light, I Mani, J Rennie TREC, 2000 | 25 | 2000 |
| An application of machine learning to e-mail filtering J Rennie Proc. KDD-2000 Text Mining Workshop, 75-80, 2000 | 18 | 2000 |
Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
