Publications, Working Papers, and Presentations

 Machine Learning 
 Heuristic Algorithms 
 Economics & Computation 
 Language Models 
 Social Impact 
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
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2024

2023

2022

  • The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models. G. d'Eon, J. d'Eon, J. Wright, K. Leyton-Brown. ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT), 2022.
  • The Perils of Learning Before Optimizing. C. Cameron, J. Hartford, T. Lundy, K. Leyton-Brown. AAAI Conference on Artificial Intelligence, 2022.
  • Huge Frozen Language Models as Readers for Open-Domain Question Answering. Y. Levine, O. Ram, D. Jannai, B. Lenz, S. Shalev-Shwartz, A. Shashua, K. Leyton-Brown, Y. Shoham. Workshop on Knowledge Retrieval and Language Models at the Thirty-Ninth International Conference on Machine Learning (ICML), 2022.
  • Kudu: An Electronic Agricultural Marketplace in Uganda. N. Newman, N. Immorlica, K. Leyton-Brown, B. Lucier, J. Quinn, R. Ssekibuule. In Artificial Intelligence for Social Impact, M. Tambe, F. Fang, B. Wilder (editors), Springer, 2022.
  • The New Faculty Highlights Program at AAAI-21. K. Leyton-Brown, Mausam, Q. Yang. In AI Magazine, Volume 43, Issue 4, Page 343, 2022.
  • Standing on the Shoulders of Giant Frozen Language Models. Y. Levine, I. Dalmedigos, O. Ram, Y. Zeldes, D. Jannai, D. Muhlgay, Y. Osin, O. Lieber, B. Lenz, S. Shalev-Shwartz, A. Shashua, K. Leyton-Brown, Y. Shoham. Working Paper, 2022.
  • MRKL Systems: A Modular, Neuro-Symbolic Architecture that Combines Large Language Models, External Knowledge Sources and Discrete Reasoning. E. Karpas, O. Abend, Y. Belinkov, B. Lenz, O. Lieber, N. Ratner, Y. Shoham, H. Bata, Y. Levine, K. Leyton-Brown, D. Muhlgay, N. Rozen, E. Schwartz, G. Shachaf, S. Shalev-Shwartz, A. Shashua, M. Tenenholtz. Working Paper, 2022.
  • Incentives and Markets. K. Leyton-Brown (moderator), Susan Athey, Vincent Conitzer, Nicole Immorlica, Sendhil Mullainathan, Hal Varian. Panel at the ACM's 75th Anniversary Celebration, 2022.

2021

  • PMI-Masking: Principled Masking of Correlated Spans. Y. Levine, B. Lenz, O. Lieber, O. Abend, K. Leyton-Brown, M. Tennenholtz, Y. Shoham. International Conference on Learning Representations (ICLR), 2021. Selected as a Spotlight Presentation.
  • Valid Causal Inference with (Some) Invalid Instruments. J. Hartford, V. Veitch, D. Sridhar, K. Leyton-Brown. International Conference on Machine Learning (ICML), 2021.
  • Automated Configuration and Selection of SAT Solvers. H. Hoos, F. Hutter, K. Leyton-Brown. Chapter 12 in Handbook of Satisfiability, Second Edition, A. Biere, M. Heule, H. van Maaren, T. Walsh (editors), Volume 336 of Frontiers in Artificial Intelligence and Applications, IOS Press, 2021.
  • Mechanical TA 2: A System for Peer Grading with TA Support. H. Zarkoob, F. Abdolhosseini, K. Leyton-Brown. Working paper, 2021.
  • Learning under Invariable Bayesian Safety. G. Bahar, O. Ben-Porat, K. Lecacyton-Brown, M. Tennenholtz. Working paper, 2021.

2020

  • ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool. G. Weisz, A. György, W. Lin, D. Graham, K. Leyton-Brown, C. Szepesvári, B. Lucier. Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020.
  • Exemplar Guided Active Learning. J. Hartford, K. Leyton-Brown, H. Raviv, D. Padnos, S. Lev, B. Lenz. Thirty-Fourth Conference on Neural Information Processing Systems (NeurIPS), 2020.
  • Dynamic Weighted Matching with Heterogeneous Arrival and Departure Rates. N. Collina, N. Immorlica, K. Leyton-Brown, B. Lucier, N. Newman. Sixteenth Conference on Web and Internet Economics (WINE), pp. 17–30, 2020.
  • Fiduciary Bandits. G. Bahar, O. Ben-Porat, K. Leyton-Brown, M. Tennenholtz. Thirty-seventh International Conference on Machine Learning (ICML), 2020.
  • A Formal Separation Between Strategic and Nonstrategic Behavior. J. Wright, K. Leyton-Brown. Twenty-First ACM Conference on Economics and Computation (ACM-EC), 2020.
  • Incentive Auction Design Alternatives: A Simulation Study. N. Newman, K. Leyton-Brown, P. Milgrom, I. Segal. ACM Conference on Economics and Computation (ACM-EC), 2020. Chosen as the Exemplary Paper in the AI and Computation Track.
  • Predicting Propositional Satisfiability via End-to-End Learning.C. Cameron, R. Chen, J. Hartford, K. Leyton-Brown. Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020.
  • Report-Sensitive Spot-Checking in Peer-Grading Systems. H. Zarkoob, H. Fu, K. Leyton-Brown. Nineteenth International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020.
  • Smarter Parking: Using AI to Identify Parking Inefficiencies in Vancouver. D. Graham, S. K. Sarraf, T. Lundy, A. MohammadMehr, S. Uppal, T.Y. Lee, H. Zarkoob, S.D. Kominers, K. Leyton-Brown. Working paper, 2020.
  • Making an Impact? A Tale of Two Projects. K. Leyton-Brown. Artificial Intelligence Seminar, University of Alberta, June 2020.
  • AI Debate at AAAI 2020: "Academic AI researchers should focus their attention on research problems that are not of immediate interest to industry". With Carla Gomes, Subbarao Kambhampati, Eric Horvitz, Tuomas Sandholm. Debate at AAAI Conference on Artificial Intelligence (AAAI), New York, February 2020.
  • Artificial Intelligence: The Journey So Far, and the World in 2029. K. Leyton-Brown. Green College Special Lecture, University of British Columbia, January 2020.

2019

  • Incentivizing Evaluation with Peer Prediction and Limited Access to Ground Truth. X. Gao, J. Wright, K. Leyton-Brown. Artificial Intelligence Journal (AIJ), volume 275, pp. 618–638, October 2019.
  • Level-0 Models for Predicting Human Behavior in Games. J. Wright, K. Leyton-Brown. Journal of Artificial Intelligence Research (JAIR), volume 64, pp. 357–383, February 2019.
  • Operations Research Enables Auction to Repurpose Television Spectrum for Next-Generation Wireless Technologies. J. Kiddoo, E. Kwerel, S. Javid, M. Dunford, G. Epstein, C. Meisch, K. Hoffman, B. Smith, A. Coudert, R. Sultana, J. Costa, S. Charbonneau, M. Trick, I. Segal, K. Leyton-Brown, N. Newman, A. Fréchette, D. Menon, P. Salasznyk. INFORMS Journal on Applied Analytics (IJAA), volume 49, number 1, pp. 7–22, February 2019.
  • Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration. R. Kleinberg, K. Leyton-Brown, B. Lucier, D. Graham‚. Thirty-Third Conference on Neural Information Processing Systems (NeurIPS), 2019.
  • Allocation for Social Good: Auditing Mechanisms for Utility Maximization. T. Lundy, A. Wei, H. Fu, S. Kominers, K. Leyton-Brown. Twentieth ACM Conference on Economics and Computation (ACM-EC), pp. 785–803, 2019.
  • Auto-WEKA: Automatic Model Selection and Hyperparameter Optimization in WEKA. L. Kotthoff, C. Thornton, H. Hoos, F. Hutter, K. Leyton-Brown. Chapter 4 in F. Hutter, L. Kotthoff, J. Vanschoren, Automated Machine Learning, pages 81–95, Springer, 2019.
  • Algorithm Configuration: Learning in the Space of Algorithm Designs. F. Hutter, K. Leyton-Brown. A half-day tutorial at the 36th International Conference on Machine Learning (ICML), 2019.
  • AI Debate at AAAI 2019: "The AI community today should continue to focus mostly on ML methods". With Oren Etzioni, Michael Littman, Jennifer Neville, Peter Stone. Debate at AAAI Conference on Artificial Intelligence (AAAI), Waikiki, 2019.

2018

  • Deep Optimization for Spectrum Repacking. N. Newman, A. Fréchette, K. Leyton-Brown. Communications of the ACM (CACM), volume 61, number 1, pp. 97–104 , January 2018.
  • Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates. K. Eggensperger, M. Lindauer, H. Hoos, F. Hutter, K. Leyton-Brown. Machine Learning Journal (MLJ), to appear, 2018.
  • Deep Models of Interactions Across Sets. D. Graham, J. Hartford, K. Leyton-Brown, S. Ravanbakhsh. Thirty-fifth International Conference on Machine Learning (ICML), 2018.
  • Quantifying Algorithmic Improvements over Time. A. Fréchette, L. Kotthoff, T. Rahwan, H. Hoos, K. Leyton-Brown, T. Michalak. Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI), Special Track on the Evolution of the Contours of AI, 2018.
  • Designing and Evolving an Electronic Agricultural Marketplace in Uganda. N. Newman, K. Leyton-Brown, N. Immorlica, L. Bergquist, B. Lucier, J. Quinn, C. McIntosh, R. Ssekibuule. ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS), 2018.
  • Artificial intelligence in 2027. M. Gini, N. Agmon, F. Giunchiglia, S. Koenig, K. Leyton-Brown. AI Matters. Volume 4 Issue 1, pp. 10–20, Spring 2018.
  • Selection and Configuration of Parallel Portfolios. M. Lindauer, H. Hoos, F. Hutter, K. Leyton-Brown. Chapter 15 in Youssef Hamadi, Lakhdar Sais (editors). Handbook of Parallel Constraint Reasoning, pages 581–614, Springer, 2017.
    • Official version: DOIDOI
  • AI Debate at AAAI 2018: "Advances in Machine Learning have displaced the need for logic in AI". With Tom Dietterich, Bart Selman (for); Gary Marcus, Francesca Rossi (against). Debate at AAAI Conference on Artificial Intelligence (AAAI), New Orleans, 2018.

2017

  • Economics and Computer Science of a Radio Spectrum Reallocation. K. Leyton-Brown, P. Milgrom, I. Segal. Proceedings of the National Academy of Sciences (PNAS), volume 114, number 28, pp. 7202–7209, 2017.
  • Predicting Human Behavior in Unrepeated, Simultaneous-Move Games. J. Wright, K. Leyton-Brown. Games and Economic Behavior (GEB), volume 106, pp. 16–37, November 2017.
  • Computational Analysis of Perfect-Information Position Auctions. D. Thompson, K. Leyton-Brown. Games and Economic Behavior (GEB), volume 102, pp. 583–623, March 2017.
  • Auto-WEKA 2.0: Automatic model and hyperparameter selection in WEKA. L. Kotthoff, C. Thornton, F. Hutter, H. Hoos, K. Leyton-Brown. Journal of Machine Learning Research (JMLR), volume 18, number 25, pp. 1–5, 2017.
  • Automatic Construction of Parallel Portfolios via Algorithm Configuration. M. Lindauer, H. Hoos, K. Leyton-Brown, T. Schaub. Artificial Intelligence Journal (AIJ), volume 244, pp. 272–290, March 2017.
  • The Configurable SAT Solver Challenge (CSSC). F. Hutter, M. Lindauer, A. Balint, S. Bayless, H. Hoos, K. Leyton-Brown. Artificial Intelligence Journal (AIJ), volume 243, pp. 1–25, February 2017.
  • Efficiency Through Procrastination: Approximately Optimal Algorithm Configuration with Runtime Guarantees. B. Kleinberg, K. Leyton-Brown, B. Lucier. International Joint Conference on Artificial Intelligence (IJCAI), 2017.
  • Deep IV: A Flexible Approach for Counterfactual Prediction. J. Hartford, G. Lewis, K. Leyton-Brown, M. Taddy. International Conference on Machine Learning (ICML), 2017.
  • The Positronic Economist: A Computational System for Analyzing Economic Mechanisms. D. Thompson, N. Newman, K. Leyton-Brown. Conference on Artificial Intelligence (AAAI), 2017.
  • Resource Graph Games: A Compact Representation for Games with Structured Strategy Spaces. A. Jiang,
    H. Chan, K. Leyton-Brown. Conference on Artificial Intelligence (AAAI), 2017.
  • Selection and Configuration of Parallel Portfolios. M. Lindauer, H. Hoos, F. Hutter, K. Leyton-Brown. Chapter 15 in Y. Hamadi, L. Sais (eds.), Handbook of Parallel Constraint Reasoning, Springer, pp. 581–614, 2017.
  • Solving the Station Repacking Problem. A. Fréchette, N. Newman, K. Leyton-Brown. Chapter 38 in M. Bichler & J. Goeree (eds.), Handbook of Spectrum Auction Design, Cambridge University Press, pp. 813–827, 2017.
    • Official version: DOIDOI
  • The End of Work? A Conversation with Toby Walsh and Stefan Hajkowicz. AI Lounge, Melbourne, Australia, August 2017.
  • AI in 2027. With Maria Gini (chair), Noa Agmon, Sven König, Fausto Giunchiglia. Panel discussion at International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, 2017.
  • Kudu: A Mobile Market for Agricultural Trade in Uganda. K. Leyton-Brown. Based on joint work with L. Bergquist, N. Immorlica, B. Lucier, C. McIntosh, N. Newman, R. Ssekibuule, J. Quinn. 2017.

2016

  • SATenstein: Automatically Building Local Search SAT Solvers from Components. A. KhudaBukhsh, L. Xu, H. Hoos, K. Leyton-Brown. Artificial Intelligence Journal (AIJ), volume 232, pp. 20–42, March 2016.
    • Preprint: PDFPDF
    • Official version: DOIDOI
  • ASlib: A Benchmark Library for Algorithm Selection. B. Bischl, P. Kerschke, L. Kotthoff, M. Lindauer, Y. Malitsky, A. Fréchette, H. Hoos, F. Hutter, K. Leyton-Brown, K. Tierney, J. Vanschoren. Artificial Intelligence Journal (AIJ), volume 237, pp. 41–58, August 2016.
  • Deep Learning for Predicting Human Strategic Behavior. J. Hartford, J. Wright, K. Leyton-Brown. Oral presentation at Conference on Neural Information Processing Systems (NIPS), 2016.
  • Multilinear Games. H. Chan, A. Jiang, K. Leyton-Brown, R. Mehta. Conference on Web and Internet Economics (WINE), 2016.
    • Paper (published version): PDFPDF
    • Paper (long version): PDFPDF
  • Solving the Station Repacking Problem. A. Fréchette, N. Newman, K. Leyton-Brown. Conference on Artificial Intelligence (AAAI), 2016.
  • Using the Shapley Value to Analyze Algorithm Portfolios. A. Fréchette, L. Kotthoff, T. Rahwan, H. Hoos, K. Leyton-Brown, T. Michalak. Conference on Artificial Intelligence (AAAI), 2016.
  • Bias in Algorithm Portfolio Performance Evaluation. C. Cameron, H. Hoos, K. Leyton-Brown. International Joint Conference on Artificial Intelligence (IJCAI), 2016.
  • Quantifying the Similarity of Algorithm Configurations. L. Xu, A. Khudabukhsh, H. Hoos, K. Leyton-Brown. Learning and Intelligent Optimization Conference (LION10), 2016.
  • Deep Counterfactual Prediction using Instrumental Variables. J. Hartford, G. Lewis, K. Leyton-Brown, M. Taddy. Workshop on Inference and Learning of Hypothetical and Counterfactual Interventions in Complex Systems at the Conference on Neural Information Processing Systems (NIPS), 2016.
  • Incentivizing Evaluation via Limited Access to Ground Truth: Peer-Prediction Makes Things Worse. X. A. Gao, J. R. Wright, K. Leyton-Brown. Workshop on Algorithmic Game Theory and Data Science at the 17th ACM Conference on Electronic Commerce, 2016.
  • Artificial Intelligence and Life in 2030. P. Stone, R. Brooks, E. Brynjolfsson, R. Calo, O. Etzioni, G. Hager, J. Hirschberg, S. Kalyanakrishnan, E. Kamar, S. Kraus, K. Leyton-Brown, D. Parkes, W. Press, A. Saxenian, J. Shah, M. Tambe, A. Teller. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, 2016.
  • Understanding the Empirical Hardness of NP-Hard Problems. K. Leyton-Brown. Talk at Simons Institute for the Theory of Computing, Berkeley, Boot Camp on Algorithms and Uncertainty, August 2016.
    • Part I (empirical hardness models): YoutubeYouTube
    • Part II (applications to algorithm configuration and selection): YoutubeYouTube
  • The Incentive Auction: a Practical Success Story for Policy Impact of AI. K. Leyton-Brown. Talk at Technology Policy Institute Panel on Economic and Policy Implications of AI, National Press Club, Washington DC.

2015

  • Mechanical TA: Partially Automated High-Stakes Peer Grading. J. Wright, C. Thornton, K. Leyton-Brown. ACM Technical Symposium on Computer Science Education (ACM-SIGCSE), 2015
  • Efficient Benchmarking of Hyperparameter Optimizers via Surrogates. K. Eggensperger, F. Hutter, H. Hoos, K. Leyton-Brown. Conference on Artificial Intelligence (AAAI), 2015.
  • Algorithm Runtime Prediction: Methods & Evaluation (Extended Abstract). F. Hutter, L. Xu, H. Hoos, K. Leyton-Brown. International Joint Conference on Artificial Intelligence (IJCAI) Journal Track, 2015. This is an extended abstract of our journal paper, published in a special track at IJCAI on papers that recently appeared in AIJ without having previously appeared as conference publications. It was competitively peer reviewed for IJCAI.

2014

  • Understanding the Empirical Hardness of NP-Complete Problems. K. Leyton-Brown, H. Hoos, F. Hutter, L. Xu. Communications of the Association for Computing Machinery (CACM), volume 57, issue 5, pp. 98–107, May 2014.
  • Algorithm Runtime Prediction: Methods & Evaluation. F. Hutter, L. Xu, H. Hoos, K. Leyton-Brown. Artificial Intelligence (AIJ), volume 206, pp. 79–111, January 2014. Received the  AIJ Prominent Paper Award 2021.
    • Preprint: PDFPDF
    • Official version: DOIDOI
  • Level-0 Meta-Models for Predicting Human Behavior in Games. J. Wright, K. Leyton-Brown. ACM Conference on Economics and Computation (ACM-EC), 2014.
  • Reasoning about Optimal Stable Matchings under Partial Information. B. Rastegari, A. Condon, N. Immorlica, R. Irving, K. Leyton-Brown. ACM Conference on Economics and Computation (ACM-EC), 2014.
  • An Efficient Approach for Assessing Hyperparameter Importance. F. Hutter, H. Hoos, K. Leyton-Brown. International Conference on Machine Learning (ICML), 2014.
  • Improved Features for Runtime Prediction of Domain-Independent Planners. C. Fawcett, M. Vallati, F. Hutter, J. Hoffmann, H. Hoos, K. Leyton-Brown. International Conference on Automated Planning and Scheduling (ICAPS), 2014.
  • Algorithm Configuration in the Cloud: A Feasibility Study. D. Geschwender, F. Hutter, L. Kotthoff, Y. Malitsky, H. Hoos and K. Leyton-Brown. Learning and Intelligent Optimization Conference (LION7), 2014.
  • AClib: a Benchmark Library for Algorithm Configuration. F. Hutter, M. Lopez-Ibanez, C. Fawcett, M. Lindauer, H. Hoos, K. Leyton-Brown, T. Stützle. Learning and Intelligent Optimization Conference (LION7), 2014.
  • Surrogate Benchmarks for Hyperparameter Optimization.K. Eggensperger, F. Hutter, H. Hoos, K. Leyton-Brown. Workshop on Meta-Learning and Algorithm Selection (MetaSel), co-located with ECAI, 2014.
  • Pragmatic Algorithmic Game Theory. K. Leyton-Brown. Keynote address at ACM Conference on Economics and Computation (ACM-EC), June 12, 2014.
  • Feasibility Checking for Spectrum Repacking: Methodologies and Test Results. K. Leyton-Brown. Talk at FCC LEARN Workshop on Feasibility Checking During Repacking Process, February 21, 2014.

2013

  • Polynomial-time Computation of Exact Correlated Equilibrium in Compact Games. A. Jiang, K. Leyton-Brown. Games and Economics Behavior (GEB), (23 pages), 2013. A journal version of our 2011 ACM-EC conference paper.
    • Preprint: PDFPDF
    • Official version: DOIDOI
  • A Mobile Market for Agricultural Trade in Uganda. R. Ssekibuule, J. Quinn, K. Leyton-Brown. ACM Symposium on Computing for Development (ACM-DEV), 2013.
  • Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms. C. Thornton, F. Hutter, H. Hoos, K. Leyton-Brown. ACM Conference on Knowledge Discovery and Data Mining (KDD), (9 pages), 2013.
  • Two-Sided Matching with Partial Information. B. Rastegari, A. Condon, N. Immorlica, K. Leyton-Brown. ACM Conference on Electronic Commerce (ACM-EC), pp. 733–750, 2013.
  • Revenue Optimization in the Generalized Second-Price Auction. D. Thompson, K. Leyton-Brown. ACM Conference on Electronic Commerce (ACM-EC), pp. 837–852, 2013.
  • Empirical Analysis of Plurality Election Equilibria. D. Thompson, O. Lev, K. Leyton-Brown, J. Rosenschein. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 391–398, 2013. A preliminary version appeared at the International Workshop on Computational Social Choice (COMSOC), 2012.
  • Identifying Key Algorithm Parameters and Instance Features using Forward Selection. F. Hutter, H. Hoos, K. Leyton-Brown. Learning and Intelligent Optimization Conference (LION7), (15 pages), 2013.
  • Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters. K. Eggensperger, M. Feurer, F. Hutter, J. Bergstra, J. Snoek, H. Hoos, K. Leyton-Brown. Workshop on Bayesian Optimization, co-located with NIPS, 2013.
  • An Evaluation of Sequential Model-Based Optimization for Expensive Blackbox Functions. F. Hutter, H. Hoos, K. Leyton-Brown. Black-Box-Optimization-Benchmarking (BBOB) workshop at the ACM Genetic and Evolutionary Computation Conference (ACM-GECCO), pp. 1209–1216, 2013.
  • Bayesian Optimization with Censored Response Data. F. Hutter, H. Hoos, K. Leyton-Brown. Working paper, 2013. An extended version of our NIPS workshop paper from 2011.
  • Mechanism Design and Auctions. K. Leyton-Brown, Y. Shoham. Chapter 7 in Multiagent Systems, Second Edition, G. Weiss (editor), pp. 285–327, MIT Press, 2013.
  • Games, Markets & Algorithms: Reasoning about an Interconnected World. A nontechnical overview of my recent work in game theory and mechanism design, UBC CS Faculty Lecture Series, March 21, 2013.
  • The Viability of Exact Feasibility Checking. Talk at the Stanford Institute for Economic Policy Research Conference on the design of the U.S. Incentive Auction for reallocating spectrum between wireless telecommunications and television broadcasting, February 25, 2013.

2012

  • Approximately Revenue-Maximizing Auctions for Deliberative Agents. D. Thompson, K. Leyton-Brown, L.E. Celis, A.R. Karlin, C.T. Nguyen. Conference of the Association for the Advancement of Artificial Intelligence (AAAI), (7 pages), 2012.
  • Predicting Satisfiability at the Phase Transition. L. Xu, H. Hoos, K. Leyton-Brown. Conference of the Association for the Advancement of Artificial Intelligence (AAAI), (7 pages), 2012.
  • The Deployment-to-Saturation Ratio in Security Games. M. Jain, K. Leyton-Brown, M. Tambe. Conference of the Association for the Advancement of Artificial Intelligence (AAAI), (7 pages), 2012.
  • Behavioral Game-Theoretic Models: A Bayesian Framework For Parameter Analysis. J. Wright, K. Leyton-Brown. Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 921–930, 2012.
  • Evaluating Component Solver Contributions in Portfolio-based Algorithm Selectors. L. Xu, F. Hutter, K. Leyton-Brown, H. Hoos. Conference on Theory and Applications of Satisfiability Testing (SAT), pp. 228–241, 2012.
  • Parallel Algorithm Configuration. F. Hutter, H.H. Hoos, K. Leyton-Brown. Learning and Intelligent Optimization Conference (LION6), pp. 55–70, 2012. 
  • TRUSTS: Scheduling Randomized Patrols for Fare Inspection in Transit Systems. Z. Yin, A.X. Jiang, M.P. Johnson, M. Tambe, K. Leyton-Brown, T. Sandholm, J.P. Sullivan, C. Kiekintveld. Conference on Innovative Applications of Artificial Intelligence (IAAI), (8 pages), 2012. A preliminary version appeared as Towards Optimal Patrol Strategies for Fare Inspection in Transit Systems, at the 2012 AAAI Spring Symposium on Game Theory for Security, Sustainability and Health.
  • SATzilla2012: Improved Algorithm Selection Based on Cost-sensitive Classification Models. L. Xu, F. Hutter, J. Shen, H. Hoos, K. Leyton-Brown. International Conference on Theory and Applications of Satisfiability Testing (SAT), SAT Challenge 2012: Solver Descriptions, 2012.
  • Algorithm Configuration for Portfolio-based Parallel SAT-Solving. H. Hoos, K. Leyton-Brown, T. Schaub, M. Schneider. Workshop on Combining Constraint Solving with Mining and Learning (CoCoMile) at the European Conference on Artificial Intelligence (ECAI), (5 pages), 2012.

2011

  • Revenue Monotonicity in Deterministic, Dominant-Strategy Combinatorial Auctions.  B. Rastegeri, A. Condon, K. Leyton-Brown. Artificial Intelligence (AIJ), volume 175, issue 2, pp. 441–456, February 2011. This is an extended version of our 2007 AAAI paper.
    • Preprint: PDFPDF
    • Official journal paper: DOIDOI
  • Action-Graph Games.  A.X. Jiang, K. Leyton-Brown, N.A.R. Bhat. Games and Economic Behavior, volume 71, issue 1, pp. 141–173, January 2011.
    • Preprint: PDFPDF
    • Official journal paper: DOIDOI
    • Software download:  HTMLAGG project page
    • Slides from Santa Fe Institue Workshop on Decentralized Control in Systems of Strategic Actors: PDFPDF
  • A General Framework for Computing Optimal Correlated Equilibria in Compact Games. A. X. Jiang, K. Leyton-Brown. Workshop on Internet and Network Economics (WINE 2011), pp. 218–229, 2011.
  • Computing Nash Equilibria of Action-Graph Games via Support Enumeration. D. Thompson, S. Leung, K. Leyton-Brown. Workshop on Internet and Network Economics (WINE 2011), pp. 338–350, 2011.
  • Polynomial-time Computation of Exact Correlated Equilibrium in Compact Games. A.X. Jiang, K. Leyton-Brown. ACM Electronic Commerce Conference (ACM-EC), pp. 119–126, 2011. Received the best student paper award. Short version appeared in SIGecom Exchanges, volume 10, number 1, pages 6–8, 2011.
  • Dominant-Strategy Auction Design for Agents with Uncertain, Private Values. D. Thompson, K. Leyton-Brown. Conference of the Association for the Advancement of Artificial Intelligence (AAAI), 2011.
    • Paper: PDFPDF
    • Presentation from Workshop on Innovations in Algorithmic Game Theory, Hebrew University, Jerusalem: PDFPDF; YoutubeYouTube video
  • Modeling and Monitoring Crop Disease in Developing Countries. J. Quinn, K. Leyton-Brown, E. Mwebaze. Conference of the Association for the Advancement of Artificial Intelligence (AAAI), Computational Sustainability and AI Track, 2011.
  • Sequential Model-Based Optimization for General Algorithm Configuration. F. Hutter, H.H. Hoos, K. Leyton-Brown. Learning and Intelligent OptimizatioN Conference (LION5), pp. 507–523, January 2011. Received the runner-up best paper award. 
  • HAL: A Framework for the Automated Design and Analysis of High-Performance Algorithms. C. Nell, C. Fawcett, H.H. Hoos, K. Leyton-Brown. Learning and Intelligent OptimizatioN Conference (LION5), pp. 600–615, 2011.
  • Linear solvers for nonlinear games: using pivoting algorithms to find Nash equilibria in n-player games. James Wright, Albert Xin Jiang, K. Leyton-Brown. SIGecom Exchanges, volume 10, number 1, pages 9–12, 2011.
  • Bayesian Optimization with Censored Response Data. F. Hutter, H. Hoos, K. Leyton-Brown. Workshop on Bayesian Optimization, Experimental Design, and Bandits, at the Neural Information Processing Systems Conference (NIPS), (5 pages), December 2011.
  • Hydra-MIP: Automated Algorithm Configuration and Selection for Mixed Integer Programming. L. Xu, F. Hutter, H.H. Hoos, K. Leyton-Brown. RCRA workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion at the International Joint Conference on Artificial Intelligence (IJCAI), Barcelona, July 2011.
  • Detailed SATzilla Results from the Data Analysis Track of the 2011 SAT Competition. L. Xu, F. Hutter, H. Hoos, K. Leyton-Brown. In Fourteenth International Conference on Theory and Applications of Satisfiability Testing, SAT 2011 Competition: Data Analysis Track, 2011.
  • Empirical Hardness Models: A Statistical Approach to Describing Hardness in Practice. K. Leyton-Brown. Presentation at the Workshop on Beyond Worst-Case Analysis at Stanford University, California.
  • Algorithms for Making Good Decisions. K. Leyton-Brown. A nontechnical introduction to my research, presented at Calumet College, York University.
  • Future Directions in Algorithmic Game Theory. Panel: S. Hart, K. Leyton-Brown, S. Micali, E. Tardos, V. Vazirani. At the Workshop on Innovations in Algorithmic Game Theory, Hebrew University, Jerusalem, June 2011.

2010

  • Tradeoffs in the Empirical Evaluation of Competing Algorithm Designs F. Hutter, H.H. Hoos, K. Leyton-Brown.  Annals of Mathematics and Artificial Intelligence (AMAI), Special Issue on Learning and Intelligent Optimization, volume 60, number 1, pp. 65–89, October 2010.
  • Algorithmic Game Theory and Artificial Intelligence. E. Elkind, K. Leyton-Brown. Artificial Intelligence Magazine, volume 31, number 4, pp. 9–12, 2011.
  • Bayesian Action-Graph Games. A. X. Jiang, K. Leyton-Brown. Conference on Neural Information Processing Systems (NIPS), 2010.
  • Computing Pure Strategy Nash Equilibria in Compact Symmetric Games. C. Ryan, A. X. Jiang, K. Leyton-Brown. ACM Conference on Electronic Commerce (ACM-EC), 2010.
  • Beyond Equilibrium: Predicting Human Behavior in Normal Form Games. J. Wright, K. Leyton-Brown. Conference of the Association for the Advancement of Artificial Intelligence (AAAI-10), 2010.
    • Paper: PDFPDF
    • Slides from AAAI, Atlanta (by James Wright): PDFPDF
  • Hydra: Automatically Configuring Algorithms for Portfolio-Based Selection. L. Xu, H.H. Hoos, K. Leyton-Brown. Conference of the Association for the Advancement of Artificial Intelligence (AAAI-10), 2010.
  • Time-Bounded Sequential Parameter Optimization. F. Hutter, H.H. Hoos, K. Leyton-Brown, K. Murphy.  Learning and Intelligent Optimization Conference (LION4), pp. 281–298, 2010. Received the runner-up best paper award.
    • Paper: PDFPDF
    • Official Version: DOIDOI
    • Slides from LION, Venice (by Frank Hutter): PDFPDF
  • Automated Configuration of Mixed Integer Programming Solvers. F. Hutter, H.H. Hoos, K. Leyton-Brown. International Conference on Integration of Artificial Intelligence and Operations Research techniques in Constraint Programming (CPAIOR), pp. 186–202, 2010.
    • Paper: PDFPDF
    • Official Version: DOIDOI
    • Slides from CPAIOR, Bologna (by Frank Hutter): PDFPDF
  • Sequential Model-Based Parameter Optimisation: an Experimental Investigation of Automated and Interactive Approaches. F. Hutter, T. Bartz-Beielstein, H.H. Hoos, K. Leyton-Brown, K.P. Murphy. Chapter 15 in Experimental Methods for the Analysis of Optimization Algorithms, T. Bartz-Beielstein, M. Chiarandini, L. Paquete, M. Preuss (editors), pages 361–411. Springer, 2010.
  • Computational Mechanism Analysis: Towards a "CPLEX for Mechanisms". K. Leyton-Brown. Presentation at the inauguration of the Center for Research in the Foundations of Electronic Markets, Aarhus University, Denmark.
    • Slides from CFEM, Aarhus: PDFPDF

2009

Multiagent Systems

 

2008
Essentials of Game Theory

 

  • SATzilla: Portfolio-based Algorithm Selection for SAT. L. Xu, F. Hutter, H.H. Hoos, K. Leyton-Brown. Journal of Artificial Intelligence Research (JAIR), volume 32, pp. 565–606, June 2008. Received the 2010 IJCAI-JAIR Best Paper Prize.
  • Tractable Computational Methods for Finding Nash Equilibria of Perfect-Information Position Auctions. D. Thompson, K. Leyton-Brown. Fourth Workshop on Ad Auctions, ACM Conference on Electronic Commerce (EC'08), 2008.
  • Collusion in Unrepeated, First-Price Auctions with an Uncertain Number of Participants. K. Leyton-Brown, M. Tennenholtz, N.A.R. Bhat, Y. Shoham. Please cite as UBC CS Technical Report TR-2008-10, 2008.
  • Empirically Evaluating Multiagent Learning Algorithms. E. Zawadzki, A. Lipson, K. Leyton-Brown. Working Paper, November 2008.
  • From CATS to SAT: Modeling Empirical Hardness to Understand and Solve Hard Computational Problems.  K. Leyton-Brown. Presentation at 3rd Multiagent Resource Allocation (MARA) Symposium, Amsterdam, 2008.
    • Abstract: PDFPDF
    • Slides from MARA, Amsterdam: PDFPDF

2007

  • Bidding Agents for Online Auctions with Hidden Bids. A. Jiang, K. Leyton-Brown.  Machine Learning Journal,  volume 67, number 1–2, pp. 117–143, May 2007.  A short version was presented with the title Computing Bidders' Valuation Distributions in Online Auctions at the Game Theory and Decision Theory Workshop at the International Conference on Artificial Intelligence (IJCAI-05). 
  • SATzilla-07: The Design and Analysis of an Algorithm Portfolio for SAT. L. Xu, F. Hutter, H.H. Hoos, K. Leyton-Brown. Principles and Practice of Constraint Programming (CP), Providence, 2007.
  • Hierarchical Hardness Models for SAT. L. Xu, H.H. Hoos, K. Leyton-Brown. Principles and Practice of Constraint Programming (CP), Providence, 2007.
  • Computing Pure Nash Equilibria in Symmetric Action Graph Games. A. Jiang, K. Leyton-Brown. Association for the Advancement of Artificial Intelligence (AAAI), Vancouver, 2007.
  • Valuation Uncertainty and Imperfect Introspection in Second-Price Auctions. D. Thompson, K. Leyton-Brown. Association for the Advancement of Artificial Intelligence (AAAI), Vancouver, 2007.
    • Paper: PDFPDF; BibTeXBIB
    • Slides from DIMACS Workshop on Auctions with Transaction Costs, Rutgers (by Dave Thompson): PDFPDF
  • Revenue Monotonicity in Combinatorial Auctions. B. Rastegari, A. Condon, K. Leyton-Brown. Association for the Advancement of Artificial Intelligence (AAAI), Vancouver, 2007.
    • Paper: PDFPDF; BibTeXBIB
    • Slides from Computational Social Systems and the Internet, Dagstuhl, 2007: PDFPDF
  • Empirically Testing Decision Making in TAC SCM. E. Zawadzki, K. Leyton-Brown. AAAI-07 Workshop on Trading Agent Design and Analysis (TADA-07), Vancouver, 2007.
    • Paper: PDFPDF; BibTeXBIB
    • Slides from TADA, Vancouver (by Erik Zawadzki): PDFPDF
  • A Tutorial on the Proof of the Existence of Nash Equilibria. A. Jiang and K. Leyton-Brown. UBC CS Technical Report TR-2007-25, 2007.

2006

2005

2004

  • Understanding Random SAT: Beyond the Clauses-to-Variables Ratio.  E. Nudelman,  K. Leyton-Brown, H.H. Hoos, A. Devkar, Y. Shoham.  Principles and Practice of Constraint Programming (CP-04), Toronto, 2004.
  • Computing Nash Equilibria of Action-Graph Games. N. Bhat, K. Leyton-Brown.  Uncertainty in Artificial Intelligence (UAI-2004), Banff, 2004.  Short versions the World Congress on Game Theory (Games 2004) and the Stony Brook Game Theory Conference, 2004.
  • Run the GAMUT: A Comprehensive Approach to Evaluating Game-Theoretic Algorithms.  E. Nudelman, J. Wortman, Y. Shoham and K. Leyton-Brown.  International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-04), New York, 2004.  Short versions appeared at the World Congress on Game Theory (Games 2004) and the Stony Brook Game Theory Conference, 2004.
  • SATzilla: An Algorithm Portfolio for SAT.  E. Nudelman, A. Devkar, Y. Shoham, K. Leyton-Brown, H.H. Hoos.  International Conference on Satisfiability Testing (SAT-2004) (short paper, unrefereed), Vancouver, 2004.  Presented at the International Symposium on Artificial Intelligence and Mathematics (AI+Math 2004).

2003

2002

  • Learning the Empirical Hardness of Optimization Problems: the case of combinatorial auctions.  K. Leyton-Brown, E. Nudelman, Y. Shoham.  Principles and Practice of Constraint Programming (CP-02), Ithaca, 2002. It was also presented at Electronic Market Design, 2002.
  • Bidding Clubs in First-Price Auctions: K. Leyton-Brown, Y. Shoham, M. Tennenholtz.  American Association for Artificial Intelligence (AAAI-02), Edmonton, 2002.
  • Incentive Mechanisms for Smoothing Out a Focused Demand for Network Resources: K. Leyton-Brown, R. Porter, S. Venkataraman, B. Prabhakar.  ACM Computer Communications Review, volume 26, pp. 237–250, 2002.  A short version appeared in the ACM Conference on Electronic Commerce (EC'01) with the title Smoothing Out Focused Demand for Network Resources; the work was also presented at ITCom 2001. 
    • Preprint: PDFPDF; BibTeXBIB
    • Official journal paper: DOIDOI
    • Slides from ITCom 2001, Seattle: PDFPDF 
  • Response to Milgrom and Ausubel's Comments on the Second Wye River Package Bidding Conference. K. Leyton-Brown. Published on the Federal Communication Commission's Combinatorial Bidding Conference 2001 website, January 2002.
    • Paper: PDFPDF; BibTeXBIB
    • Milgrom and Ausubel's Comments on the Second Wye River Package Bidding Conference: PDFPDF
    • FCC's Combinatorial Bidding Conference 2001 website: HTMLLink

2001

  • Incentives for Sharing in Peer-to-Peer Networks: P. Golle, K. Leyton-Brown, I. Mironov, M. Lillibridge.  The full version appeared in Workshop on Electronic Commerce (WELCOM'01), Heidelberg, 2001.  The short version appeared in ACM Conference on Electronic Commerce (EC'01), Tampa, 2001.
  • Smoothing Out Focused Demand for Network Resources. K. Leyton-Brown, R. Porter, S. Venkataraman, B. Prabhakar.  ACM Conference on Electronic Commerce (EC'01), Tampa, 2001. 
  • Auctions, Auction Theory, and Hard Computational Problems in Auctions.  Presentation at Cornell workshop on computational hardness and auctions, June 2001.  Most of this talk was adapted from slides by Shoham, Tennenholtz and Wellman.
    • Slides from Cornell workshop: PDFPDF

2000

  • Towards a Universal Test Suite for Combinatorial Auctions: K. Leyton-Brown, M. Pearson, Y. Shoham.  ACM Conference on Electronic Commerce (EC'00), Minneapolis, 2000. 
  • Bidding Clubs: Institutionalized Collusion in Auctions: K. Leyton-Brown, M. Tennenholtz, Y. Shoham.  ACM Conference on Electronic Commerce (EC'00), Mineapolis, 2000.  A preliminary version was presented at Games 2000, Bilbao. 
  • An Algorithm for Multi-Unit Combinatorial Auctions: K. Leyton-Brown, M. Tennenholtz, Y. Shoham.  American Association for Artificial Intelligence (AAAI-2000), Austin, 2000. It was also presented at the World Congress on Game Theory (Games-2000), Bilbao, 2000, and the International Symposium on Mathematical Programming (ISMP-2000), Atlanta, 2000.

1999

Last updated April 17, 2024