Publications

[2016] [2015] [2014] [2013] [2012] [2011] [2010] [2009] [2008]
[2007] [2006] [2005] [2004] [2003] [2002] [2001] [2000] [1999]
[1998] [1997] [1996] [1995] [1994] [1993] [1992]


2016

  • S. Hill, Z. Zhou, L. Saul, and H. Shacham (2016). On the (in)effectiveness of mosaicing and blurring as tools for document redaction. In Proceedings of the 16th Privacy Enhancing Technologies Symposium(PETS-16), pages 404-418. Darmstadt, Germany. [pdf]

2015

  • S. Liu, I. Foster, S. Savage, G. M. Voelker, and L. K. Saul (2015). Who is .com? Learning to parse WHOIS records. In Proceedings of the ACM Internet Measurement Conference (IMC-15), pages 369-380. Tokyo, Japan. [pdf]

  • T. Halvorson, M. F. Der, I. Foster, S. Savage, L. K. Saul, and G. M. Voelker (2015). From .academy to .zone: an analysis of the new TLD land rush. In Proceedings of the ACM Internet Measurement Conference (IMC-15), pages 381-394. Tokyo, Japan. [pdf]

  • K. Singh, S. Smallen, S. Tilak, and L. K. Saul (2015). Failure analysis and prediction for the CIPRES science gateway. In Proceedings of the 10th Gateway Computing Environments Workshop (GCE-15). Boulder, CO.

2014

  • D. Wang, M. F. Der, M. Karami, L. K. Saul, D. McCoy, S. Savage, G. M. Voelker (2014). Search and seizure: the effectiveness of interventions on SEO campaigns. In Proceedings of the 2014 Internet Measurement Conference (IMC-14), pages 359-372. Vancouver, BC, Canada. [pdf]

  • M. F. Der, L. K. Saul, S. Savage, and G. M. Voelker (2014). Knock it off: profiling the online storefronts of counterfeit merchandise. In Proceedings of the Twentieth ACM Conference on Knowledge Discovery and Data Mining (KDD-14), pages 1759-1768. New York, NY. [pdf]

  • D.-K. Kim, M. Der, and L. K. Saul (2014). A Gaussian latent variable model for large margin classification of labeled and unlabeled data. In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS-14), pages 484-492. Reykjavik, Iceland. [pdf] [supplement] [code]

  • D.-K. Kim, G. M. Voelker, and L. K. Saul (2014). Topic modeling of hierarchical corpora. [arxiv]

2013

  • D.-K. Kim, G. M. Voelker, and L. K. Saul (2013). A variational approximation for topic modeling of hierarchical corpora. In Proceedings of the 30th International Conference on Machine Learning (ICML-13), pages 55-63. Atlanta, GA. [pdf]

  • X. Ma, P. Huang, X. Jin, P. Wang, S. Park, D. Shen, Y. Zhou, L. K. Saul, and G. M. Voelker (2013). eDoctor: automatically diagnosing abnormal battery drain issues on smartphones. In Proceedings of the 10th ACM/USENIX Symposium on Networked Systems Design and Implementation (NSDI-13), pages 57-70. Lombard, IL. [pdf]

2012

  • M. F. Der and L. K. Saul (2012). Latent coincidence analysis: a hidden variable model for distance metric learning. In P. Bartlett, F. C. N. Pereira, C. J. C. Burges, L. Bottou, K. Q. Weinberger (eds.), Advances in Neural Information Processing Systems 25, pages 3239-3247. Lake Tahoe, CA. [pdf]

2011

  • V. Mahadevan, C.-W. Wong, T. T. Liu, N. Vasconcelos and L. K. Saul (2011). Maximum covariance unfolding: manifold learning for bimodal data. In J. Shawe-Taylor, R.S. Zemel, P. Bartlett, F. C. N. Pereira, and Culotta (eds.), Advances in Neural Information Processing Systems 24, pages 918-926. Granada, Spain. [pdf]

  • S. N. Bannur, L. K. Saul, and S. Savage (2011). Judging a site by its content: learning the textual, structural, and visual features of malicious Web pages. In Proceedings of the 4th ACM Workshop on Artificial Intelligence and Security (AISEC-11), pages 1-10. Chicago, IL. [pdf]

  • D.-K. Kim, M. Motoyama, G. M. Voelker, and L. K. Saul (2011). Topic modeling of freelance job postings to monitor web service abuse. In Proceedings of the 4th ACM Workshop on Artificial Intelligence and Security (AISEC-11), pages 11-20. Chicago, IL. [pdf]

  • J. T. Ma, L. K. Saul, S. Savage, and G. M. Voelker (2011). Learning to detect malicious URLs. ACM Transactions on Intelligent Systems and Technology 2(3), pages 30:1-24. [pdf]

  • L. J. P. van der Maaten, M. Welling, and L. K. Saul (2011). Hidden-unit conditional random fields. In Proceedings of the Fourteenth International Conference on Artificial Intelligence & Statistics (AISTATS-11), pages 479-488. Fort Lauderdale, FL. [pdf]

2010

  • D. J. Hu, L. van der Maaten, Y. Cho, L. K. Saul, and S. Lerner (2010). Latent variable models for predicting file dependencies in large-scale software development. In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, and A. Culotta (eds.), Advances in Neural Information Processing Systems 23, pages 865-873. [pdf]
  • J. T. Ma, A. Kulesza, M. Dredze, K. Crammer, L. K. Saul, and F. C. N. Pereira (2010). Exploiting feature covariance in high-dimensional online learning. In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), pages 493-500. Sardinia, Italy. [pdf]

  • K. Q. Weinberger, F. Sha, and L. K. Saul (2010). Convex optimizations for distance metric learning and pattern classification. IEEE Signal Processing Magazine 27(3): 146-158. [pdf]

  • M. Bozorgi, L. K. Saul, S. Savage, and G. M. Voelker (2010). Beyond heuristics: learning to classify vulnerabilities and predict exploits. In Proceedings of the Sixteenth ACM Conference on Knowledge Discovery and Data Mining (KDD-10), pages 105-113. Washington, DC. [pdf]

  • Y. Cho and L. K. Saul (2010). Large margin classification in infinite neural networks. Neural Computation 22(10): 2678-2697. [pdf]

  • C.-C. Cheng, F. Sha, and L. K. Saul (2010). Online learning and acoustic feature adaptation in large margin hidden Markov models. IEEE Journal of Selected Topics in Signal Processing 4(6): 926-942. [pdf]

2009

2008

2007

2006

2005

2004

2003

  • L. K. Saul and S. T. Roweis (2003). Think globally, fit locally: unsupervised learning of low dimensional manifolds. Journal of Machine Learning Research 4:119-155. [ ps.gz, pdf, matlab]

  • L. K. Saul, F. Sha, and D. D. Lee (2003). Statistical signal processing with nonnegativity constraints. In Proceedings of the Eighth European Conference on Speech Communication and Technology, volume 2, pages 1001-1004, Geneva, Switzerland. [pdf]

  • J. H. Ham, D. D. Lee, and L. K. Saul (2003). Learning high dimensional correspondences from low dimensional manifolds. In Proceedings of the ICML 2003 Workshop on The Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining, pages 34-41, Washington, D.C. [pdf]

  • F. Sha, L. K. Saul, and D. D. Lee (2003). Multiplicative updates for large margin classifiers. In Proceedings of the Sixteenth Annual Conference on Computational Learning Theory, pages 188-202, Washington D.C. [pdf]

  • A. I. Schein, L. K. Saul, and L. Ungar (2003). A generalized linear model for principal component analysis of binary data. In C. M. Bishop and B. J. Frey (eds.), Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, pages 14-21, Key West, FL. [pdf]

  • L. K. Saul, D. D. Lee, C. L. Isbell, and Y. LeCun (2003). Real time voice processing with audiovisual feedback: toward autonomous agents with perfect pitch. In S. Becker, S. Thrun, and K. Obermayer (eds.), Advances in Neural Information Processing Systems 15, pages 1205-1212. MIT Press: Cambridge, MA. [pdf, matlab]

  • F. Sha, L. K. Saul, and D. D. Lee (2003). Multiplicative updates for nonnegative quadratic programming in support vector machines. In S. Becker, S. Thrun, and K. Obermayer (eds.), Advances in Neural Information Processing Systems 15, pages 1065-1073. MIT Press: Cambridge, MA. [pdf]

2002

  • S. T. Roweis, L. K. Saul and G. E. Hinton (2002). Global coordination of locally linear models. In T. G. Dietterich, S. Becker, and Z. Ghahramani (eds.), Advances in Neural Information Processing Systems 14, pages 889-896. MIT Press: Cambridge, MA. [ps.gz]

  • L. K. Saul and D. D. Lee (2002). Multiplicative updates for classification by mixture models. In T. G. Dietterich, S. Becker, and Z. Ghahramani (eds.), Advances in Neural Information Processing Systems 14, pages 897-904. MIT Press: Cambridge, MA. [ps.gz]

2001

2000

1999

1998

  • M. S. Kearns and L. K. Saul (1998). Large deviation methods for approximate probabilistic inference. In G. Cooper and S. Moral (eds.), Proceedings of the Fourteenth Annual Conference on Uncertainty in Artificial Intelligence, pages 311-319. Morgan Kaufmann: San Mateo, CA. [pdf]

  • L. K. Saul and M. G. Rahim (1998). Modeling acoustic correlations by factor analysis. In M. I. Jordan, M. S. Kearns, and S. A. Solla (eds.), Advances in Neural Information Processing Systems 10, pages 749-756. MIT Press: Cambridge, MA.

  • L. K. Saul and M. G. Rahim (1998). Automatic segmentation of continuous trajectories with invariance to nonlinear warpings of time. In J. Shavlik (ed.), Proceedings of the Fifteenth International Conference on Machine Learning, pages 506-514, Madison, WI.

1997

  • L. K. Saul and F. C. N. Pereira (1997). Aggregate and mixed-order Markov models for statistical language processing. In C. Cardie and R. Weischedel (eds.), Proceedings of the Second Conference on Empirical Methods in Natural Language Processing, pages 81-89. ACM Press, New York, NY. [pdf]

  • L. K. Saul and M. I. Jordan (1997). Mixed memory Markov models. In P. Smyth and D. Madigan (eds.), Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics (AISTATS-97), Fort Lauderdale, FL.

  • M. I. Jordan, Z. Ghahramani, and L. K. Saul (1997). Hidden Markov decision trees. In M. C. Mozer, M. I. Jordan, and T. Petsche (eds.), Advances in Neural Information Processing Systems 9, pages 501-507. MIT Press: Cambridge, MA. [pdf]

  • L. K. Saul and M. I. Jordan (1997). A variational principle for model-based morphing. In M. C. Mozer, M. I. Jordan, and T. Petsche (eds.), Advances in Neural Information Processing Systems 9, pages 267-273. MIT Press: Cambridge, MA. [pdf]

1996

  • L. K. Saul, T. Jaakkola, and M. Jordan (1996). Mean field theory for sigmoid belief networks. Journal of Artificial Intelligence Research 4:61-76. [abstract, ps.Z, pdf]

  • L. K. Saul and M. I. Jordan (1996). Exploiting tractable substructures in intractable networks. In D. S. Touretzky, M. C. Mozer, and S. E. Hasselmo (eds.), Advances in Neural Information Processing Systems 8, pages 486-492. MIT Press: Cambridge, MA. [pdf]

  • L. K. Saul and S. Singh (1996). Learning curve bounds for Markov decision processes with undiscounted rewards. In Proceedings of the Ninth Annual Workshop on Computational Learning Theory, pages 147-156. ACM Press: New York, NY. [pdf]

  • T. Jaakkola, L. K. Saul, and M. I. Jordan (1996). Fast learning by bounding likelihoods in sigmoid type belief networks. In D. S. Touretzky, M. C. Mozer, and S. E. Hasselmo (eds.), Advances in Neural Information Processing Systems 8, pages 528-534. MIT Press: Cambridge, MA. [pdf]

1995

  • L. K. Saul and M. I. Jordan (1995). Boltzmann chains and hidden Markov models. In G. Tesauro, D. S. Touretzky, and T. K. Leen (eds.), Advances in Neural Information Processing Systems 7, pages 435-442. MIT Press: Cambridge, MA. [pdf]

  • L. K. Saul and S. Singh (1995). Markov decision processes in large state spaces. In Proceedings of the Eighth Annual Workshop on Computational Learning Theory, pages 281-288. ACM Press, New York, NY.

1994

1993

1992