Kevin Leyton-brown
30 papers · 2010–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (5) πΊοΈ Taxonomy Completionist (20) π Conference Polyglot (8)
π
Conference Polyglot
(8)
π
Academic Marathon
(15)
πΊοΈ
Taxonomy Completionist
(20)
π±
Topic Pioneer
π§¬
Topic Evolution
π
Grand Slam
π
Keyword Champion
(2)
ποΈ
Keyword Collector
(127)
π
Trend Setter
π
Century Club
(28)
π₯
Unstoppable
(12)
β‘
Prolific Year
(5)
Conferences
AAAI (7)
ICML (7)
NIPS (6)
IJCAI (5)
ICLR (2)
ACL (1)
EACL (1)
JMLR (1)
Top co-authors
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