← Authors

Kevin Leyton-brown

30 papers · 2010–2026 · 8 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (9) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (15) πŸ—ΊοΈ Taxonomy Completionist (20) 🌱 Topic Pioneer 🧬 Topic Evolution πŸ† Grand Slam πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (127) πŸ“ˆ Trend Setter πŸ’Ž Century Club (28) πŸ”₯ Unstoppable (12) ⚑ Prolific Year (5)

Conferences

AAAI (7) ICML (7) NIPS (6) IJCAI (5) ICLR (2) ACL (1) EACL (1) JMLR (1)

Top co-authors

Devon Graham (4) Yoav Levine (4) Jason Hartford (4) Greg d'Eon (3) Jason S Hartford (3) Chris Cameron (3) Holger H. Hoos (3) Brendan Lucier (3) Taylor Lundy (3) Frank Hutter (3)

Keywords

algorithm configuration (5) game theory (5) deep learning (4) utility function (3) hyperparameter optimization (3) stochastic optimization (3) strategic behavior (2) neural network (2) mechanism design (2) end-to-end learning (2) bayesian inference (2) online algorithm (2) bayesian optimization (2) language model (2) instrumental variable (2) factual accuracy (1) attention mechanism (1) binary classification (1) behavioral economics (1) model selection (1)

Papers

ElementaryNet: A Non-Strategic Neural Network for Predicting Human Behavior in Normal-Form Games AAAI 2026
Practical, Utilitarian Algorithm Configuration AAAI 2026
Utilitarian Algorithm Configuration for Infinite Parameter Spaces ICLR 2025
STEER: Assessing the Economic Rationality of Large Language Models ICML 2024
How to Evaluate Behavioral Models AAAI 2024
Pay to (Not) Play: Monetizing Impatience in Mobile Games AAAI 2024
Generating Benchmarks for Factuality Evaluation of Language Models EACL 2024
Utilitarian Algorithm Configuration NIPS 2023
Formalizing Preferences Over Runtime Distributions ICML 2023
Parallel Context Windows for Large Language Models ACL 2023
Better Peer Grading through Bayesian Inference AAAI 2023
The Perils of Learning Before Optimizing AAAI 2022
Valid Causal Inference with (Some) Invalid Instruments ICML 2021
PMI-Masking: Principled masking of correlated spans ICLR 2021
Predicting Propositional Satisfiability via End-to-End Learning AAAI 2020
Incentivizing Evaluation with Peer Prediction and Limited Access to Ground Truth (Extended Abstract) IJCAI 2020
Exemplar Guided Active Learning NIPS 2020
ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool NIPS 2020
Fiduciary Bandits ICML 2020
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration NIPS 2019
Quantifying Algorithmic Improvements over Time IJCAI 2018
Deep Models of Interactions Across Sets ICML 2018
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA JMLR 2017
Deep IV: A Flexible Approach for Counterfactual Prediction ICML 2017
Efficiency Through Procrastination: Approximately Optimal Algorithm Configuration with Runtime Guarantees IJCAI 2017
Bias in Algorithm Portfolio Performance Evaluation IJCAI 2016
Deep Learning for Predicting Human Strategic Behavior NIPS 2016
Algorithm Runtime Prediction: Methods and Evaluation (Extended Abstract) IJCAI 2015
An Efficient Approach for Assessing Hyperparameter Importance ICML 2014
Bayesian Action-Graph Games NIPS 2010