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Kevin Jamieson

38 papers · 2014–2025 · 8 conferences · across top CS/AI conferences

Achievements

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+10 more ↓ 🌍 Conference Polyglot (8) πŸ—ΊοΈ Taxonomy Completionist (16) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer πŸƒ Academic Marathon (11)
πŸƒ Academic Marathon (11) 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (9) πŸ”¬ Deep Specialist (13) πŸ† Keyword Champion (3) πŸ—ƒοΈ Keyword Collector (57) πŸ’Ž Century Club (38) ⚑ Prolific Year (11) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (6)

Conferences

AISTATS (11) ICML (11) COLT (6) NIPS (6) ACL (1) JMLR (1) RSS (1) UAI (1)

Papers

Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals ICML 2025 Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries COLT 2025 Active learning of neural population dynamics using two-photon holographic optogenetics NIPS 2024 Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL NIPS 2024 Nearly Minimax Optimal Submodular Maximization with Bandit Feedback NIPS 2024 Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning NIPS 2024 An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models ACL 2024 CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning NIPS 2024 Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning NIPS 2024 A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity AISTATS 2024 Optimal Exploration is no harder than Thompson Sampling AISTATS 2024 Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits AISTATS 2024 Fair Active Learning in Low-Data Regimes UAI 2024 Demonstrating Large-Scale Package Manipulation via Learned Metrics of Pick Success RSS 2023 Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games AISTATS 2023 Improved Active Multi-Task Representation Learning via Lasso ICML 2023 Best Arm Identification with Safety Constraints AISTATS 2022 Beyond No Regret: Instance-Dependent PAC Reinforcement Learning COLT 2022 Active Multi-Task Representation Learning ICML 2022 First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach ICML 2022 Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes ICML 2022 Nearly Optimal Algorithms for Level Set Estimation AISTATS 2022 Experimental Design for Regret Minimization in Linear Bandits AISTATS 2021 High-dimensional Experimental Design and Kernel Bandits ICML 2021 Improved Corruption Robust Algorithms for Episodic Reinforcement Learning ICML 2021 Improved Algorithms for Agnostic Pool-based Active Classification ICML 2021 Task-Optimal Exploration in Linear Dynamical Systems ICML 2021 Active Learning for Identification of Linear Dynamical Systems COLT 2020 The True Sample Complexity of Identifying Good Arms AISTATS 2020 Estimating the Number and Effect Sizes of Non-null Hypotheses ICML 2020 Firing Bandits: Optimizing Crowdfunding ICML 2018 Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization JMLR 2018 The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime COLT 2017 Non-stochastic Best Arm Identification and Hyperparameter Optimization AISTATS 2016 Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls AISTATS 2016 Best-of-K-bandits COLT 2016 Sparse Dueling Bandits AISTATS 2015 lil’ UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits COLT 2014