Luis Ortiz's Publications

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Ph.D. Thesis

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

    • Papers and Preprints

  • Luis E. Ortiz. Correlated Equilibria and Probabilistic Inference in Graphical Models. Manuscript, August 25, 2009.
    [PDF]
    This is a manuscript I wrote back in 2009 which contains the foundation, including theoretical results and computational implications, behind three pieces of work.
    Detailed info
  • Luis E. Ortiz and Mohammad T. Irfan. Tractable Algorithms for Approximate Nash Equilibria in Generalized Graphical Games with Tree Structure. In In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), February 4-9, 2017, San Francisco, CA, USA., pp. 635--641, 2017. AAAI Press.
    [PDF]
  • Technical Report (Long Version): Luis E. Ortiz and Mohammad T. Irfan. FPTAS for Mixed-Strategy Nash Equilibria in Tree Graphical Games and Their Generalizations. arXiv:1602.05237 [cs.GT], Original: February 2016; Last Update: February 2017.
  • Luis E. Ortiz. RESEARCH NOTE: On Sparse Discretization for Graphical Games. Journal of Artificial Intelligence Research (JAIR). Accepted January 6, 2017.
  • Luis E. Ortiz. On Sparse Discretization for Graphical Games. arXiv:1411.3320 [cs.AI], November 2014.
    Original: December 2002.
  • Hau Chan, Michael Ceyko, and Luis Ortiz. Interdependent Defense Games with Applications to Internet Security at the Level of Autonomous Systems. Games, 8(1), 13, 2017.
    This article belongs to the Special Issue on Decision Making for Network Security and Privacy.
    An extended version of the following conference papers:
  • Hau Chan and Luis E. Ortiz. Computing Nash Equilibrium in Interdependent Defense Games. In AAAI Conference on Artificial Intelligence, 2015.
    [URL]
  • Hau Chan, Michael Ceyko, and Luis E. Ortiz. Interdependent Defense Games: Modeling Interdependent Security under Deliberate Attacks. In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI), August 2012.
    [PDF]
    A previous related version:
  • 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.
    [PDF]
  • Jean Honorio and Luis Ortiz. Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data. Journal of Machine Learning Research (JMLR), 16(Jun):1157--1210, 2015.
    [Abstract] [PDF]
  • Preprint: arXiv:1206.3713 [cs.LG]
  • A journal-length version: submitted to arXiv on June 16, 2012 (paper [PDF]).
  • Last conference version: submitted March 30, 2012 to UAI 2012 (main paper [PDF]; supplementary material [PDF]).
  • First conference version: entitled, Learning Influence Games, initially submitted June 1, 2010 to NIPS 2010.
  • Mohammad T. Irfan and Luis E. Ortiz. Causal Strategic Inference in Networked Microfinance Economies. In, Advances in Neural Information Processing Systems (NIPS) 27, Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence, and K.Q. Weinberger, Editors, Pages 1161--1169, 2014. Curran Associates, Inc.
    [PDF]
    Also appeared as an invited poster at Workshop on Transactional Machine Learning and E-Commerce, Neural Information Processing Systems (NIPS) Dec. 12, 2014, Montreal, Quebec, Canada
    Other related versions:
  • Mohammad T. Irfan and Luis E. Ortiz. Causal Inference in Game-Theoretic Settings with Applications to Microfinance Markets.
    In The 26th International Conference on Game Theory, part of the Stony Brook Game Theory Summer Festival 2015, July 2015.
  • A Game-Theoretic Model of Microfinance Markets (Poster). In New York Computer Science and Economics (NYCE) Day, September 2011.
  • Hau Chan and Luis E. Ortiz. Learning Game Parameters from MSNE: An Application to Learning IDS Games.
    In The 26th International Conference on Game Theory, part of the Stony Brook Game Theory Summer Festival 2015, July 2015.
    [PDF] Presentation Information
  • Luis E. Ortiz. Graphical Potential Games. Preprint: arXiv:1505.01539 [cs.GT], May 2015.
    First submission: July 30, 2010 to WINE 2010.
    In The 26th International Conference on Game Theory, part of the Stony Brook Game Theory Summer Festival 2015, July 2015.
    [PDF] Presentation Information Slides
  • Kota Yamaguchi, M. Hadi Kiapour, Luis E. Ortiz, and Tamara L. Berg. Retrieving Similar Styles to Parse Clothing. Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on, Vol. 37, no. 5, pp. 1028--1040, May 2015.
    URL
    Extends and subsumes the following conference version:
  • 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.
    [PDF]
  • Ayon Chakraborty, Luis E. Ortiz, and Samir R. Das. Network-side Positioning of Cellular-band Devices with Minimal Effort. In IEEE INFOCOM 2015, 2015.
    [PDF]
  • Joshua Belanich and Luis E. Ortiz. Some Open Problems in Optimal AdaBoost and Decision Stumps. Preprint: arXiv:1505.06999 [cs.LG], May 2015.
  • Joshua Belanich and Luis E. Ortiz. On the Convergence Properties of Optimal AdaBoost. Preprint: arXiv:1212.1108 [cs.LG], version 2, April 2015.
    Original: December 2012.
  • Hau Chan and Luis E. Ortiz. Computing Nash Equilibrium in Interdependent Defense Games. In AAAI Conference on Artificial Intelligence, 2015.
    [URL]
  • Hau Chan and Luis E. Ortiz. Computing Nash Equilibria in Generalized Interdependent Security Games. In, Advances in Neural Information Processing Systems (NIPS) 27, Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence, and K.Q. Weinberger, Editors, Pages 2735--2743, 2014. Curran Associates, Inc.
    [PDF]
    Also appeared as an invited poster at Workshop on Transactional Machine Learning and E-Commerce, Neural Information Processing Systems (NIPS) Dec. 12, 2014, Montreal, Quebec, Canada
  • Kota Yamaguchi, Tamara L. Berg, and Luis E. Ortiz. Chic or Social? -- Multimodal Popularity Analysis in Online Fashion Networks. In ACM Multimedia (MM), 2014. Short paper.
  • Mohammad T. Irfan and Luis E. Ortiz. On Influence, Stable Behavior, and the Most Influential Individuals in Networks: A Game-Theoretic Approach. Artificial Intelligence. Volume 215, Pages 79-119, October 2014.
    ISSN 0004-3702,     http://dx.doi.org/10.1016/j.artint.2014.06.004
    URL
    Preprint as Technical Report: arXiv:1303.2147 [cs.GT], 2013.
    Other related versions and workshop presentations:
  • Mohammad T. Irfan and Luis E. Ortiz. A Game-Theoretic Approach to Influence in Networks. In AAAI Conference on Artificial Intelligence (AAAI), 2011.
    [PDF]
  • Causal Strategic Inference in Networks (Poster). In Workshop on Information and Decision in Social Networks (WIDS), November 2012.
    [PDF]
  • 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.
  • Utpal Paul, Luis Ortiz, Samir R. Das, Giordano Fusco, and Milind Madhav Buddhikot. Learning Probabilistic Models of Cellular Network Traffic with Applications to Resource Management. In IEEE DySPAN, 2014.
  • 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.
  • 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.
    [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: Sun Aug 20 09:18:05 EDT 2017