Kevin Leyton-Brown

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 95

Top Venues

CoRR

AAAI

Artif. Intell.

Publications

Hedayat Zarkoob, Siddharth Nand, Kevin Leyton-Brown, Giulia Toti
Agora: Motivating and Measuring Engagement in Large-Class Discussions. ITiCSE (1) (2024)
Ilia Kuznetsov, Osama Mohammed Afzal, Koen Dercksen, Nils Dycke, Alexander Goldberg, Tom Hope, Dirk Hovy, Jonathan K. Kummerfeld, Anne Lauscher, Kevin Leyton-Brown, Sheng Lu, Mausam, Margot Mieskes, Aurélie Névéol, Danish Pruthi, Lizhen Qu, Roy Schwartz, Noah A. Smith, Thamar Solorio, Jingyan Wang, Xiaodan Zhu, Anna Rogers, Nihar B. Shah, Iryna Gurevych
What Can Natural Language Processing Do for Peer Review? CoRR (2024)
Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, Yoav Shoham
Generating Benchmarks for Factuality Evaluation of Language Models. EACL (1) (2024)
Chris Cameron, Jason S. Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown
UNSAT Solver Synthesis via Monte Carlo Forest Search. CPAIOR (1) (2024)
Devon R. Graham, Kevin Leyton-Brown
Utilitarian Algorithm Configuration for Infinite Parameter Spaces. CoRR (2024)
Taylor Lundy, Narun Raman, Hu Fu, Kevin Leyton-Brown
Pay to (Not) Play: Monetizing Impatience in Mobile Games. AAAI (2024)
Narun Raman, Taylor Lundy, Samuel Amouyal, Yoav Levine, Kevin Leyton-Brown, Moshe Tennenholtz
Rationality Report Cards: Assessing the Economic Rationality of Large Language Models. CoRR (2024)
Greg d'Eon, Sophie Greenwood, Kevin Leyton-Brown, James R. Wright
How to Evaluate Behavioral Models. AAAI (2024)
Greg d'Eon, Neil Newman, Kevin Leyton-Brown
Understanding Iterative Combinatorial Auction Designs via Multi-Agent Reinforcement Learning. CoRR (2024)
Hedayat Zarkoob, Kevin Leyton-Brown
Mechanical TA 2: Peer Grading with TA and Algorithmic Support. SIGCSE (1) (2024)
Kevin Leyton-Brown, Yoav Shoham
Understanding Understanding: A Pragmatic Framework Motivated by Large Language Models. CoRR (2024)
Kevin Leyton-Brown, Mausam, Yatin Nandwani, Hedayat Zarkoob, Chris Cameron, Neil Newman, Dinesh Raghu
Matching papers and reviewers at large conferences. Artif. Intell. 331 (2024)
Hedayat Zarkoob, Greg d'Eon, Lena Podina, Kevin Leyton-Brown
Better Peer Grading through Bayesian Inference. AAAI (2023)
Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, Yoav Shoham
Generating Benchmarks for Factuality Evaluation of Language Models. CoRR (2023)
Devon R. Graham, Kevin Leyton-Brown, Tim Roughgarden
Utilitarian Algorithm Configuration. NeurIPS (2023)
Taylor Lundy, Narun Raman, Hu Fu, Kevin Leyton-Brown
Pay to (Not) Play: Monetizing Impatience in Mobile Games. CoRR (2023)
Devon R. Graham, Kevin Leyton-Brown, Tim Roughgarden
Utilitarian Algorithm Configuration. CoRR (2023)
Devon R. Graham, Kevin Leyton-Brown, Tim Roughgarden
Formalizing Preferences Over Runtime Distributions. ICML (2023)
Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
In-Context Retrieval-Augmented Language Models. CoRR (2023)
Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
In-Context Retrieval-Augmented Language Models. Trans. Assoc. Comput. Linguistics 11 (2023)
Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Inbal Magar, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
Parallel Context Windows for Large Language Models. ACL (1) (2023)
Greg d'Eon, Sophie Greenwood, Kevin Leyton-Brown, James R. Wright
Loss Functions for Behavioral Game Theory. CoRR (2023)
Yoav Levine, Itay Dalmedigos, Ori Ram, Yoel Zeldes, Daniel Jannai, Dor Muhlgay, Yoni Osin, Opher Lieber, Barak Lenz, Shai Shalev-Shwartz, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
Standing on the Shoulders of Giant Frozen Language Models. CoRR (2022)
Chris Cameron, Jason S. Hartford, Taylor Lundy, Tuan Truong, Alan Milligan, Rex Chen, Kevin Leyton-Brown
Monte Carlo Forest Search: UNSAT Solver Synthesis via Reinforcement learning. CoRR (2022)
Hedayat Zarkoob, Greg d'Eon, Lena Podina, Kevin Leyton-Brown
Better Peer Grading through Bayesian Inference. CoRR (2022)
Chris Cameron, Jason S. Hartford, Taylor Lundy, Kevin Leyton-Brown
The Perils of Learning Before Optimizing. AAAI (2022)
Greg d'Eon, Jason d'Eon, James R. Wright, Kevin Leyton-Brown
The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models. FAccT (2022)
Devon R. Graham, Kevin Leyton-Brown, Tim Roughgarden
Formalizing Preferences Over Runtime Distributions. CoRR (2022)
Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David C. Parkes, William H. Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, Astro Teller
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence. CoRR (2022)
Ehud Karpas, Omri Abend, Yonatan Belinkov, Barak Lenz, Opher Lieber, Nir Ratner, Yoav Shoham, Hofit Bata, Yoav Levine, Kevin Leyton-Brown, Dor Muhlgay, Noam Rozen, Erez Schwartz, Gal Shachaf, Shai Shalev-Shwartz, Amnon Shashua, Moshe Tennenholtz
MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning. CoRR (2022)
Kevin Leyton-Brown, Mausam, Yatin Nandwani, Hedayat Zarkoob, Chris Cameron, Neil Newman, Dinesh Raghu
Matching Papers and Reviewers at Large Conferences. CoRR (2022)
Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
Parallel Context Windows Improve In-Context Learning of Large Language Models. CoRR (2022)
Kevin Leyton-Brown, Mausam, Qiang Yang
The New Faculty Highlights Program at AAAI-21. AI Mag. 43 (4) (2022)
Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown
Valid Causal Inference with (Some) Invalid Instruments. ICML (2021)
Greg d'Eon, Jason d'Eon, James R. Wright, Kevin Leyton-Brown
The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models. CoRR (2021)
Hedayat Zarkoob, Farzad Abdolhosseini, Kevin Leyton-Brown
Mechanical TA 2: A System for Peer Grading with TA Support. CoRR (2021)
Chris Cameron, Jason S. Hartford, Taylor Lundy, Kevin Leyton-Brown
The Perils of Learning Before Optimizing. CoRR (2021)
Yoav Levine, Barak Lenz, Opher Lieber, Omri Abend, Kevin Leyton-Brown, Moshe Tennenholtz, Yoav Shoham
PMI-Masking: Principled masking of correlated spans. ICLR (2021)
Gal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, Moshe Tennenholtz
Learning under Invariable Bayesian Safety. CoRR (2020)
Yoav Levine, Barak Lenz, Opher Lieber, Omri Abend, Kevin Leyton-Brown, Moshe Tennenholtz, Yoav Shoham
PMI-Masking: Principled masking of correlated spans. CoRR (2020)
Jason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz
Exemplar Guided Active Learning. CoRR (2020)
Gellért Weisz, András György, Wei-I Lin, Devon R. Graham, Kevin Leyton-Brown, Csaba Szepesvári, Brendan Lucier
ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool. NeurIPS (2020)
Natalie Collina, Nicole Immorlica, Kevin Leyton-Brown, Brendan Lucier, Neil Newman
Dynamic Weighted Matching with Heterogeneous Arrival and Departure Rates. WINE (2020)
Chris Cameron, Rex Chen, Jason S. Hartford, Kevin Leyton-Brown
Predicting Propositional Satisfiability via End-to-End Learning. AAAI (2020)
Devon R. Graham, Satish Kumar Sarraf, Taylor Lundy, Ali MohammadMehr, Sara Uppal, Tae-Yoon Lee, Hedayat Zarkoob, Scott Duke Kominers, Kevin Leyton-Brown
Smarter Parking: Using AI to Identify Parking Inefficiencies in Vancouver. CoRR (2020)
Neil Newman, Kevin Leyton-Brown, Paul Milgrom, Ilya Segal
Incentive Auction Design Alternatives: A Simulation Study. EC (2020)
Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown
Valid Causal Inference with (Some) Invalid Instruments. CoRR (2020)
Jason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz
Exemplar Guided Active Learning. NeurIPS (2020)
Xi Alice Gao, James R. Wright, Kevin Leyton-Brown
Incentivizing Evaluation with Peer Prediction and Limited Access to Ground Truth (Extended Abstract). IJCAI (2020)
James R. Wright, Kevin Leyton-Brown
A Formal Separation Between Strategic and Nonstrategic Behavior. EC (2020)
Gal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, Moshe Tennenholtz
Fiduciary Bandits. ICML (2020)
Hedayat Zarkoob, Hu Fu, Kevin Leyton-Brown
Report-Sensitive Spot-Checking in Peer-Grading Systems. AAMAS (2020)
Natalie Collina, Nicole Immorlica, Kevin Leyton-Brown, Brendan Lucier, Neil Newman
Dynamic Weighted Matching with Heterogeneous Arrival and Departure Rates. CoRR (2020)
Hedayat Zarkoob, Hu Fu, Kevin Leyton-Brown
Report-Sensitive Spot-Checking in Peer-Grading Systems. CoRR (2019)
Gal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, Moshe Tennenholtz
Fiduciary Bandits. CoRR (2019)
James R. Wright, Kevin Leyton-Brown
Level-0 Models for Predicting Human Behavior in Games. J. Artif. Intell. Res. 64 (2019)
Hedayat Zarkoob, Hu Fu, Kevin Leyton-Brown
Report-Sensitive Spot-checking in Peer Grading Systems. AAMAS (2019)
Jean L. Kiddoo, Evan Kwerel, Sasha Javid, Melissa Dunford, Gary M. Epstein, Charles E. MeischJr., Karla L. Hoffman, Brian B. Smith, Anthony B. Coudert, Rudy K. Sultana, James A. Costa, Steven Charbonneau, Michael A. Trick, Ilya Segal, Kevin Leyton-Brown, Neil Newman, Alexandre Fréchette, Dinesh Menon, Paul Salasznyk
Operations Research Enables Auction to Repurpose Television Spectrum for Next-Generation Wireless Technologies. INFORMS J. Appl. Anal. 49 (1) (2019)
Robert Kleinberg, Kevin Leyton-Brown, Brendan Lucier, Devon R. Graham
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration. NeurIPS (2019)
Xi Alice Gao, James R. Wright, Kevin Leyton-Brown
Incentivizing evaluation with peer prediction and limited access to ground truth. Artif. Intell. 275 (2019)
Taylor Lundy, Alexander Wei, Hu Fu, Scott Duke Kominers, Kevin Leyton-Brown
Allocation for Social Good: Auditing Mechanisms for Utility Maximization. EC (2019)
Robert Kleinberg, Kevin Leyton-Brown, Brendan Lucier, Devon R. Graham
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration. CoRR (2019)
Katharina Eggensperger, Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown
Efficient benchmarking of algorithm configurators via model-based surrogates. Mach. Learn. 107 (1) (2018)
Maria L. Gini, Noa Agmon, Fausto Giunchiglia, Sven Koenig, Kevin Leyton-Brown
Artificial intelligence in 2027. AI Matters 4 (1) (2018)
Neil Newman, Alexandre Fréchette, Kevin Leyton-Brown
Deep optimization for spectrum repacking. Commun. ACM 61 (1) (2018)
James R. Wright, Kevin Leyton-Brown
Formalizing the Boundary Between Strategic and Nonstrategic Reasoning. CoRR (2018)
Jason S. Hartford, Devon R. Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh
Deep Models of Interactions Across Sets. ICML (2018)
Lars Kotthoff, Alexandre Fréchette, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown
Quantifying Algorithmic Improvements over Time. IJCAI (2018)
Neil Newman, Lauren Falcao Bergquist, Nicole Immorlica, Kevin Leyton-Brown, Brendan Lucier, Craig McIntosh, John A. Quinn, Richard Ssekibuule
Designing and Evolving an Electronic Agricultural Marketplace in Uganda. COMPASS (2018)
Jason S. Hartford, Devon R. Graham, Kevin Leyton-Brown, Siamak Ravanbakhsh
Deep Models of Interactions Across Sets. CoRR (2018)
David R. M. Thompson, Kevin Leyton-Brown
Computational analysis of perfect-information position auctions. Games Econ. Behav. 102 (2017)
Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy
Deep IV: A Flexible Approach for Counterfactual Prediction. ICML (2017)
Robert Kleinberg, Kevin Leyton-Brown, Brendan Lucier
Efficiency Through Procrastination: Approximately Optimal Algorithm Configuration with Runtime Guarantees. IJCAI (2017)
Marius Lindauer, Holger H. Hoos, Kevin Leyton-Brown, Torsten Schaub
Automatic construction of parallel portfolios via algorithm configuration. Artif. Intell. 244 (2017)
Chris Cameron, Holger H. Hoos, Kevin Leyton-Brown, Frank Hutter
OASC-2017: *Zilla Submission. OASC (2017)
Kevin Leyton-Brown, Paul Milgrom, Ilya Segal
Economics and computer science of a radio spectrum reallocation. Proc. Natl. Acad. Sci. USA 114 (28) (2017)
Neil Newman, Alexandre Fréchette, Kevin Leyton-Brown
Deep Optimization for Spectrum Repacking. CoRR (2017)
Katharina Eggensperger, Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown
Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates. CoRR (2017)
Albert Xin Jiang, Hau Chan, Kevin Leyton-Brown
Resource Graph Games: A Compact Representation for Games with Structured Strategy Spaces. AAAI (2017)
Neil Newman, Kevin Leyton-Brown, Paul Milgrom, Ilya Segal
Assessing Economic Outcomes in Simulated Reverse Clock Auctions for Radio Spectrum. CoRR (2017)
Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA. J. Mach. Learn. Res. 18 (2017)
Frank Hutter, Marius Lindauer, Adrian Balint, Sam Bayless, Holger H. Hoos, Kevin Leyton-Brown
The Configurable SAT Solver Challenge (CSSC). Artif. Intell. 243 (2017)
David R. M. Thompson, Neil Newman, Kevin Leyton-Brown
The Positronic Economist: A Computational System for Analyzing Economic Mechanisms. AAAI (2017)
James R. Wright, Kevin Leyton-Brown
Predicting human behavior in unrepeated, simultaneous-move games. Games Econ. Behav. 106 (2017)
Jason S. Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy
Counterfactual Prediction with Deep Instrumental Variables Networks. CoRR (2016)
Alexandre Fréchette, Lars Kotthoff, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown
Using the Shapley Value to Analyze Algorithm Portfolios. AAAI (2016)
Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren
ASlib: A benchmark library for algorithm selection. Artif. Intell. 237 (2016)
Hau Chan, Albert Xin Jiang, Kevin Leyton-Brown, Ruta Mehta
Multilinear Games. WINE (2016)
James R. Wright, Kevin Leyton-Brown
Models of Level-0 Behavior for Predicting Human Behavior in Games. CoRR (2016)
Jason S. Hartford, James R. Wright, Kevin Leyton-Brown
Deep Learning for Predicting Human Strategic Behavior. NIPS (2016)
Lin Xu, Ashiqur R. KhudaBukhsh, Holger H. Hoos, Kevin Leyton-Brown
Quantifying the Similarity of Algorithm Configurations. LION (2016)
Ashiqur R. KhudaBukhsh, Lin Xu, Holger H. Hoos, Kevin Leyton-Brown
SATenstein: Automatically building local search SAT solvers from components. Artif. Intell. 232 (2016)
Xi Alice Gao, James R. Wright, Kevin Leyton-Brown
Incentivizing Evaluation via Limited Access to Ground Truth: Peer-Prediction Makes Things Worse. CoRR (2016)
Alexandre Fréchette, Neil Newman, Kevin Leyton-Brown
Solving the Station Repacking Problem. AAAI (2016)
Chris Cameron, Holger H. Hoos, Kevin Leyton-Brown
Bias in Algorithm Portfolio Performance Evaluation. IJCAI (2016)
Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren
ASlib: A Benchmark Library for Algorithm Selection. CoRR (2015)
Albert Xin Jiang, Kevin Leyton-Brown
Polynomial-time computation of exact correlated equilibrium in compact games. Games Econ. Behav. 91 (2015)
Kevin Leyton-Brown, Panagiotis G. Ipeirotis
Introduction to the Special Issue on EC'12. ACM Trans. Economics and Comput. 3 (1) (2015)
James R. Wright, Chris Thornton, Kevin Leyton-Brown
Mechanical TA: Partially Automated High-Stakes Peer Grading. SIGCSE (2015)
Katharina Eggensperger, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown
Efficient Benchmarking of Hyperparameter Optimizers via Surrogates. AAAI (2015)

Kevin Leyton-Brown.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Kevin Leyton-Brown