Lawrence K Saul

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Geoffrey M. VoelkerUniversity of California, San DiegoVerified email at cs.ucsd.edu
Sam Roweis (Memorial)New York UniversityVerified email at buffalo.edu
Stefan SavageProfessor of Computer Science and Engineering, UC San DiegoVerified email at cs.ucsd.edu
Daniel D. LeeTisch University Professor of ECE, Cornell Tech and Executive Vice President, Samsung ResearchVerified email at alum.mit.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
John BlitzerGoogle ResearchVerified email at google.com
Diane HuEtsyVerified email at etsy.com
Fernando PereiraVP, GoogleVerified email at google.com
Jont B AllenUniversity of IL, Professor of ECEVerified email at illinois.edu
Yun MaoFacebookVerified email at fb.com
John Ashley BurgoyneUniversity of AmsterdamVerified email at uva.nl
Do-kyum KimPhD Student of Computer Science, UCSDVerified email at cs.ucsd.edu
Yuanyuan ZhouUniversity of California, San DiegoVerified email at eng.ucsd.edu
Peng HuangJohns Hopkins UniversityVerified email at cs.jhu.edu
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleVerified email at cs.toronto.edu
Laurens van der MaatenResearch Director, Facebook AI ResearchVerified email at fb.com
Ian D. FosterUC San DiegoVerified email at eng.ucsd.edu
Andrew I. ScheinWaymo - Behavior and PlanningVerified email at andrewschein.com
Lyle UngarUniversity of PennsylvaniaVerified email at cis.upenn.edu

Lawrence K Saul

Senior Research Scientist

Verified email at flatironinstitute.org - Homepage

Machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Nonlinear dimensionality reduction by locally linear embedding ST Roweis, LK Saul science 290 (5500), 2323-2326, 2000	17037	2000
An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Machine learning 37 (2), 183-233, 1999	4651	1999
Distance metric learning for large margin nearest neighbor classification. KQ Weinberger, LK Saul Journal of machine learning research 10 (2), 2009	4148	2009
Distance metric learning for large margin nearest neighbor classification KQ Weinberger, J Blitzer, L Saul Advances in neural information processing systems 18, 2005	2327	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	2123	2003
Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul International journal of computer vision 70 (1), 77-90, 2006	1152	2006
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	1021	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	684	2009
Kernel methods for deep learning Y Cho, L Saul Advances in neural information processing systems 22, 2009	682	2009
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	627	2004
Mean field theory for sigmoid belief networks LK Saul, T Jaakkola, MI Jordan Journal of artificial intelligence research 4, 61-76, 1996	543	1996
Advances in Neural Information Processing Systems 16 S Thrun, L Saul, B Schölkopf Proceedings of the 2003 Conference. illustrated edition. London, England …, 2004	367	2004
Multiplicative updates for nonnegative quadratic programming in support vector machines F Sha, L Saul, D Lee Advances in neural information processing systems 15, 2002	362	2002
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	360	2008
An introduction to nonlinear dimensionality reduction by maximum variance unfolding KQ Weinberger, LK Saul AAAI 6, 1683-1686, 2006	344	2006
Exploiting tractable substructures in intractable networks L Saul, M Jordan Advances in neural information processing systems 8, 1995	332	1995
Spectral methods for dimensionality reduction. LK Saul, KQ Weinberger, F Sha, J Ham, DD Lee Semi-supervised learning 3, 2006	330	2006
Semisupervised alignment of manifolds J Ham, D Lee, L Saul International Workshop on Artificial Intelligence and Statistics, 120-127, 2005	323	2005
Global coordination of local linear models S Roweis, L Saul, GE Hinton Advances in neural information processing systems 14, 2001	293	2001
An introduction to locally linear embedding LK Saul, ST Roweis unpublished. Available at: http://www. cs. toronto. edu/~ roweis/lle …, 2000	277	2000

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