Lawrence K Saul

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Geoffrey M. VoelkerUniversity of California, San DiegoAdresse e-mail validée de cs.ucsd.edu
Sam Roweis (Memorial)New York UniversityAdresse e-mail validée de buffalo.edu
Stefan SavageProfessor of Computer Science and Engineering, UC San DiegoAdresse e-mail validée de cs.ucsd.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleAdresse e-mail validée de eng.cam.ac.uk
Daniel D. LeeTisch University Professor of ECE, Cornell Tech and Executive Vice President, Samsung ResearchAdresse e-mail validée de alum.mit.edu
John BlitzerGoogle ResearchAdresse e-mail validée de google.com
Diane HuEtsyAdresse e-mail validée de etsy.com
Fernando PereiraVP and Engineering Fellow, GoogleAdresse e-mail validée de google.com
Jont B AllenUniversity of IL, Professor of ECEAdresse e-mail validée de illinois.edu
Yun MaoFacebookAdresse e-mail validée de fb.com
John Ashley BurgoyneAdresse e-mail validée de uva.nl
Yuanqing LinAibeeAdresse e-mail validée de aibee.co
Do-kyum KimPhD Student of Computer Science, UCSDAdresse e-mail validée de cs.ucsd.edu
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleAdresse e-mail validée de cs.toronto.edu
Yuanyuan ZhouUniversity of California, San DiegoAdresse e-mail validée de eng.ucsd.edu
Peng HuangJohns Hopkins UniversityAdresse e-mail validée de cs.jhu.edu
Laurens van der MaatenResearch Director, Facebook AI ResearchAdresse e-mail validée de fb.com
Andrew ScheinAmazon Search - Search Ranking for ProductsAdresse e-mail validée de andrewschein.com
Lyle UngarUniversity of PennsylvaniaAdresse e-mail validée de cis.upenn.edu

Lawrence K Saul

Professor of Computer Science and Engineering, UC San Diego

Adresse e-mail validée de cs.ucsd.edu - Page d'accueil

Machine learning high dimensional data analysis


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Nonlinear dimensionality reduction by locally linear embedding ST Roweis, LK Saul science 290 (5500), 2323-2326, 2000	15947	2000
An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Machine learning 37 (2), 183-233, 1999	4135	1999
Distance metric learning for large margin nearest neighbor classification. KQ Weinberger, LK Saul Journal of machine learning research 10 (2), 2009	3497	2009
Distance metric learning for large margin nearest neighbor classification KQ Weinberger, J Blitzer, LK Saul Advances in neural information processing systems, 1473-1480, 2006	2198	2006
Think globally, fit locally: unsupervised learning of low dimensional manifolds LK Saul, ST Roweis Departmental Papers (CIS), 12, 2003	2050	2003
Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul International journal of computer vision 70 (1), 77-90, 2006	1110	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	914	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	620	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	570	2004
Kernel methods for deep learning Y Cho UC San Diego, 2012	533	2012
Mean field theory for sigmoid belief networks LK Saul, T Jaakkola, MI Jordan Journal of artificial intelligence research 4, 61-76, 1996	506	1996
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	350	2008
An introduction to nonlinear dimensionality reduction by maximum variance unfolding KQ Weinberger, LK Saul AAAI 6, 1683-1686, 2006	318	2006
Semisupervised alignment of manifolds. J Ham, DD Lee, LK Saul AISTATS 120, 27, 2005	316	2005
Exploiting tractable substructures in intractable networks LK Saul, MI Jordan Advances in neural information processing systems, 486-492, 1996	314	1996
Spectral methods for dimensionality reduction. LK Saul, KQ Weinberger, F Sha, J Ham, DD Lee Semi-supervised learning 3, 2006	302	2006
Global coordination of local linear models ST Roweis, LK Saul, GE Hinton Advances in neural information processing systems 2, 889-896, 2002	286	2002
An introduction to locally linear embedding LK Saul, ST Roweis unpublished. Available at: http://www. cs. toronto. edu/~ roweis/lle …, 2000	251	2000
Aggregate and mixed-order Markov models for statistical language processing L Saul, F Pereira arXiv preprint cmp-lg/9706007, 1997	245	1997
Large margin hidden Markov models for automatic speech recognition F Sha, LK Saul Advances in neural information processing systems 19, 1249, 2007	233	2007

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