| Nonlinear dimensionality reduction by locally linear embedding ST Roweis, LK Saul science 290 (5500), 2323-2326, 2000 | 19011 | 2000 |
| Distance metric learning for large margin nearest neighbor classification. KQ Weinberger, LK Saul Journal of machine learning research 10 (2), 2009 | 5031 | 2009 |
| An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Machine learning 37, 183-233, 1999 | 4896 | 1999 |
| Distance metric learning for large margin nearest neighbor classification KQ Weinberger, J Blitzer, L Saul Advances in neural information processing systems 18, 2005 | 2567 | 2005 |
| Think globally, fit locally: unsupervised learning of low dimensional manifolds LK Saul, ST Roweis Journal of machine learning research 4 (Jun), 119-155, 2003 | 2256 | 2003 |
| Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul International journal of computer vision 70, 77-90, 2006 | 1254 | 2006 |
| Advances in neural information processing systems 16 S Thrun, L Saul, B Schölkopf Proceedings of the 2003 Conference. illustrated edition. London, England …, 2004 | 1224 | 2004 |
| Beyond blacklists: learning to detect malicious web sites from suspicious URLs J Ma, LK Saul, S Savage, GM Voelker Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 1200 | 2009 |
| Kernel methods for deep learning Y Cho, L Saul Advances in neural information processing systems 22, 2009 | 1005 | 2009 |
| Identifying suspicious URLs: an application of large-scale online learning J Ma, LK Saul, S Savage, GM Voelker Proceedings of the 26th annual international conference on machine learning …, 2009 | 812 | 2009 |
| An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Learning in graphical models, 105-161, 1998 | 793 | 1998 |
| Learning a kernel matrix for nonlinear dimensionality reduction KQ Weinberger, F Sha, LK Saul Proceedings of the twenty-first international conference on Machine learning …, 2004 | 692 | 2004 |
| Mean field theory for sigmoid belief networks LK Saul, T Jaakkola, MI Jordan Journal of artificial intelligence research 4, 61-76, 1996 | 605 | 1996 |
| Multiplicative updates for nonnegative quadratic programming in support vector machines F Sha, L Saul, D Lee Advances in neural information processing systems 15, 2002 | 392 | 2002 |
| Exploiting tractable substructures in intractable networks L Saul, M Jordan Advances in neural information processing systems 8, 1995 | 384 | 1995 |
| An introduction to nonlinear dimensionality reduction by maximum variance unfolding KQ Weinberger, LK Saul AAAI 6, 1683-1686, 2006 | 373 | 2006 |
| Fast solvers and efficient implementations for distance metric learning KQ Weinberger, LK Saul Proceedings of the 25th international conference on Machine learning, 1160-1167, 2008 | 368 | 2008 |
| Spectral methods for dimensionality reduction. LK Saul, KQ Weinberger, F Sha, J Ham, DD Lee Semi-supervised learning 3, 566-806, 2006 | 367 | 2006 |
| Semisupervised alignment of manifolds J Ham, D Lee, L Saul International Workshop on Artificial Intelligence and Statistics, 120-127, 2005 | 348 | 2005 |
| Beyond heuristics: learning to classify vulnerabilities and predict exploits M Bozorgi, LK Saul, S Savage, GM Voelker Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010 | 339 | 2010 |