Lawrence K Saul
Lawrence K Saul
Professor of Computer Science and Engineering, UC San Diego
Verified email at - Homepage
Cited by
Cited by
Nonlinear dimensionality reduction by locally linear embedding
ST Roweis, LK Saul
science 290 (5500), 2323-2326, 2000
An introduction to variational methods for graphical models
MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul
Machine learning 37 (2), 183-233, 1999
Distance metric learning for large margin nearest neighbor classification.
KQ Weinberger, LK Saul
Journal of machine learning research 10 (2), 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
Think globally, fit locally: unsupervised learning of low dimensional manifolds
LK Saul, ST Roweis
Departmental Papers (CIS), 12, 2003
Unsupervised learning of image manifolds by semidefinite programming
KQ Weinberger, LK Saul
International journal of computer vision 70 (1), 77-90, 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
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
Kernel methods for deep learning
Y Cho
University of California, San Diego, 2012
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
Mean field theory for sigmoid belief networks
LK Saul, T Jaakkola, MI Jordan
Journal of artificial intelligence research 4, 61-76, 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
An introduction to nonlinear dimensionality reduction by maximum variance unfolding
KQ Weinberger, LK Saul
AAAI 6, 1683-1686, 2006
Exploiting tractable substructures in intractable networks
LK Saul, MI Jordan
Advances in neural information processing systems, 486-492, 1996
Semisupervised alignment of manifolds
J Ham, D Lee, L Saul
International Workshop on Artificial Intelligence and Statistics, 120-127, 2005
Spectral methods for dimensionality reduction.
LK Saul, KQ Weinberger, F Sha, J Ham, DD Lee
Semi-supervised learning 3, 2006
Global coordination of local linear models
ST Roweis, LK Saul, GE Hinton
Advances in neural information processing systems 2, 889-896, 2002
An introduction to locally linear embedding
LK Saul, ST Roweis
unpublished. Available at: http://www. cs. toronto. edu/~ roweis/lle …, 2000
Mixed memory markov models: Decomposing complex stochastic processes as mixtures of simpler ones
LK Saul, MI Jordan
Machine learning 37 (1), 75-87, 1999
Aggregate and mixed-order Markov models for statistical language processing
L Saul, F Pereira
arXiv preprint cmp-lg/9706007, 1997
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