Kevin Leyton-brown
30 papers · 2010–2026 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (53) π Conference Polyglot Β· Silver π Academic Marathon Β· Full π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Deep Specialist
(10)
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Grand Slam
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Keyword Champion
(4)
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Keyword Pioneer
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Topic Evolution
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Prolific Year Β· Productive
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Unstoppable Β· Silver
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Renaissance Researcher
(7)
ποΈ
Keyword Collector
(143)
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Trend Setter
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(22)
Artificial Intelligence
(14)
Optimization & Theory
(14)
Core AI
(13)
Mathematics & Optimization
(12)
Optimization
(12)
Learning Types
(9)
Deep Learning
(5)
Core Methods
(5)
Natural Language Processing
(4)
Application Areas
(4)
Architectures
(3)
Interdisciplinary
(2)
Applications
(2)
Bayesian & Probabilistic
(2)
Keywords
algorithm configuration
(6)
game theory
(5)
utility function
(4)
deep learning
(4)
hyperparameter optimization
(3)
stochastic optimization
(3)
expected utility
(2)
instrumental variable
(2)
language model
(2)
online algorithm
(2)
end-to-end learning
(2)
bayesian optimization
(2)
neural network
(2)
bayesian inference
(2)
mechanism design
(2)
strategic behavior
(2)
factual accuracy
(1)
attention mechanism
(1)
binary classification
(1)
behavioral economics
(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
Generating Benchmarks for Factuality Evaluation of Language Models
EACL 2024
How to Evaluate Behavioral Models
AAAI 2024
Pay to (Not) Play: Monetizing Impatience in Mobile Games
AAAI 2024
STEER: Assessing the Economic Rationality of Large Language Models
ICML 2024
Better Peer Grading through Bayesian Inference
AAAI 2023
Formalizing Preferences Over Runtime Distributions
ICML 2023
Parallel Context Windows for Large Language Models
ACL 2023
Utilitarian Algorithm Configuration
NeurIPS 2023
The Perils of Learning Before Optimizing
AAAI 2022
PMI-Masking: Principled masking of correlated spans
ICLR 2021
Valid Causal Inference with (Some) Invalid Instruments
ICML 2021
Exemplar Guided Active Learning
NeurIPS 2020
Fiduciary Bandits
ICML 2020
ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool
NeurIPS 2020
Incentivizing Evaluation with Peer Prediction and Limited Access to Ground Truth (Extended Abstract)
IJCAI 2020
Predicting Propositional Satisfiability via End-to-End Learning
AAAI 2020
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration
NeurIPS 2019
Deep Models of Interactions Across Sets
ICML 2018
Quantifying Algorithmic Improvements over Time
IJCAI 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
NeurIPS 2016
Algorithm Runtime Prediction: Methods and Evaluation (Extended Abstract)
IJCAI 2015
An Efficient Approach for Assessing Hyperparameter Importance
ICML 2014
Bayesian Action-Graph Games
NeurIPS 2010