Luis Ortiz's Publications

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Ph.D. Thesis

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

    • Other Publications

  • Kota Yamaguchi, M. Hadi Kiapour, Luis E. Ortiz and Tamara L. Berg. Parsing Clothing in Fashion Photographs. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012. (to appear)
  • Abhishek Goswami, Luis E. Ortiz and Samir R. Das. WiGEM: A Learning-Based Approach for Indoor Localization. In ACM 7th International Conference on emerging Networking EXperiments and Technologies (CoNEXT), 2011.
  • Mohammad T. Irfan and Luis E. Ortiz. A Game-Theoretic Model of Microfinance Markets (Poster). In New York Computer Science and Economics (NYCE) Day, September 2011.
  • Michael Ceyko, Hau Chan and Luis E. Ortiz. Interdependent Defense Games: Modeling Interdependent Security under Deliberate Attacks (Extended Abstract). In International Conference on Game Theory, 22nd Stony Brook Game Theory Festival of the Game Theory Society, July 2011.
  • Mohammad T. Irfan and Luis E. Ortiz. A Game-Theoretic Approach to Influence in Networks. In AAAI Conference on Artificial Intelligence (AAAI), 2011.
    [PDF]
    Other related versions:
  • A Model of Strategic Behavior in Networks of Influence (Extended Abstract). In International Conference on Game Theory, 22nd Stony Brook Game Theory Festival of the Game Theory Society, July 2011.
  • A Model of Strategic Behavior in Networks of Influence (Poster). In Workshop on Information and Decision in Social Networks (WIDS), May 2011.
    [PDF]
  • Influence Games with Application to Identifying the Most Influential Nodes in Social Networks (Student "Flash" Presentation). In New York Computer Science and Economics (NYCE) Day, September 2010.
  • Kota Yamaguchi, Alexander Berg, Luis Ortiz and Tamara Berg. Who are you with and where are you going? In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011.
    [PDF]
  • Jean Honorio, Luis Ortiz, Dimitris Samaras, Nikos Paragios and Rita Goldstein. Sparse and Locally Constant Gaussian Graphical Models. In Neural Information Processing Systems (NIPS), 2009.
    [PDF]
  • Jean Honorio, Luis Ortiz, Dimitris Samaras and Rita Goldstein. Learning Brain fMRI Structure Through Sparseness and Local Constancy. In Neural Information Processing Systems, Workshop on Connectivity Inference in NeuroImaging, December 2009.
    [PDF]
  • Luis E. Ortiz. CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation. In Neural Information Processing Systems (NIPS), 2007.
    [PDF]
  • Luis E. Ortiz, Robert E. Schapire and Sham M. Kakade. Maximum Entropy Correlated Equilibria, In Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS), 2007.
    [PDF]
    A related technical report is MIT-CSAIL-TR-2006-021, 2006.
    [Postscript] [PDF]
  • 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, 2007
    [PDF]
    A related technical report is DNA Binding and Games, MIT-CSAIL-TR-2006-018, 2006.
    [PDF]
  • 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