Luis Ortiz's Publications

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Ph.D. Thesis

  • Selecting Approximately-Optimal Actions in Complex Structured Domains
    [Compressed Postscript] [PDF]

    • Papers

  • Luis Perez-Breva, Luis E. Ortiz, Chen-Hsiang Yeang, and Tommi Jaakkola. Game-Theoretic Algorithms for Protein-DNA Binding. In, Advances in Neural Information Processing Systems (NIPS) 19, 2006. To appear.
    [PDF]
    A related technical report is
    Luis Perez-Breva, Luis E. Ortiz, Chen-Hsiang Yeang, and Tommi Jaakkola. DNA Binding and Games, MIT-CSAIL-TR-2006-018, 2006.
    [PDF]
  • Luis E. Ortiz, Robert E. Schapire and Sham M. Kakade. Maximum Entropy Correlated Equilibria, MIT-CSAIL-TR-2006-021, 2006.
    [Postscript] [PDF]
    A revised version available upon request!
  • Sham M. Kakade, Michael Kearns, Luis E. Ortiz, Robin Pemantle and Siddharth Suri. Economic Properties of Social Networks, Neural Information Processing Systems (NIPS), 2004.
    [Postscript] [Compressed Postscript] [PDF]
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  • Sham M. Kakade, Michael Kearns, Yishay Mansour and Luis E. Ortiz. Competitive Algorithms for VWAP and Limit Order Trading, ACM Conference on Electronic Commerce (EC), 2004.
    [Postscript] [Compressed Postscript] [PDF]
  • Sham M. Kakade, Michael Kearns and Luis E. Ortiz. Graphical Economics, Seventeenth Annual Conference on Learning Theory (COLT), 2004.
     [Postscript] [Compressed Postscript] [PDF]
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  • Michael Kearns and Luis Ortiz. The Penn-Lehman Automated Trading Project, IEEE Intelligent Systems, Volume 18, Number 6, Pages 22-31, November/December 2003.
    IEEE version [PDF] Long version [Postscript] Long version [Compressed Postscript] Long version [PDF]
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  • Michael Kearns and Luis E. Ortiz. Algorithms for Interdependent Security Games, Neural Information Processing Systems (NIPS), 2003.
    [Postscript] [Compressed Postscript] [PDF]
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  • Sham Kakade, Michael Kearns, John Langford and Luis Ortiz. Correlated Equilibria in Graphical Games, ACM Conference on Electronic Commerce (EC), 2003.
    [Postscript] [Compressed Postscript] [PDF]
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  • Luis E. Ortiz and Michael Kearns. Nash Propagation for Loopy Graphical Games, Neural Information Processing Systems (NIPS), 2002.
    [Postscript] [Compressed Postscript] [PDF]
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  • David McAllester and Luis Ortiz. Concentration Inequalities for the Missing Mass and for Histogram Rule Error, Journal of Artificial Intelligence Research (JAIR) Special Issue on Learning Theory, Volume 4, Pages 895-911, October, 2003.
    [Abstract] Postscript [Compressed Postscript] [PDF]
    A shorther version appeared in Neural Information Processing Systems (NIPS), 2002.
    [Postscript] [Compressed Postscript] [PDF]
  • Pascal Poupart, Luis E. Ortiz and Craig Boutilier. Value-Directed Sampling Methods for Monitoring POMDPs, Proceeding of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), Pages 453-461, 2001.
    [UAI Presentation html] [Postscript] [Compressed Postscript] [PDF]
  • Milos Hauskrecht, Luis Ortiz, Ioannis Tsochantaridis, and Eli Upfal. Efficient Methods for Computing Investment Strategies for Multi-Market Commodity Trading, Applied Artificial Intelligence, Volume 15, Pages 429-452, 2001.
    [Postscript] [Compressed Postscript] [PDF]
    A shorter version appeared as Computing Global Strategies for Multi-Market Commodity Trading. Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS), 2000.
    [Postscript] [Compressed Postscript] [PDF]
  • Luis E. Ortiz and Leslie Pack Kaelbling. Adaptive Importance Sampling for Estimation in Structured Domains, Proceeding of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI), 2000.
    [Postscript] [Compressed Postscript] [PDF]
  • Luis E. Ortiz and Leslie Pack Kaelbling. Sampling Methods for Action Selection in Influence Diagrams, Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI), 2000.
    [Postscript] [Compressed Postscript] [PDF]
  • Luis E. Ortiz and Leslie Pack Kaelbling. Accelerating EM: An Empirical Study, Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI), 1999.
    [Postscript] [Compressed Postscript] [PDF]
  • Luis E. Ortiz and Leslie Pack Kaelbling. Notes on Methods Based on Maximum-Likelihood Estimation for Learning the Parameters of the Mixture-of-Gaussians Model, Technical Report CS-99-03, Department of Computer Science, Brown University, 1999.
    [Compressed Postscript] [PDF]
    • Luis E. Ortiz
    Last modified: Wed Apr 26 12:24:41 EDT 2006