Simchi-Levi, David

24 publications

NeurIPS 2025 Adaptive Variance Inflation in Thompson Sampling: Efficiency, Safety, Robustness, and Beyond Feng Zhu, David Simchi-Levi

ICML 2025 Contextual Online Decision Making with Infinite-Dimensional Functional Regression Haichen Hu, Rui Ai, Stephen Bates, David Simchi-Levi

NeurIPS 2025 Learning to Price with Resource Constraints: From Full Information to Machine-Learned Prices Ruicheng Ao, Jiashuo Jiang, David Simchi-Levi

NeurIPS 2024 Dynamic Service Fee Pricing Under Strategic Behavior: Actions as Instruments and Phase Transition Rui Ai, David Simchi-Levi, Feng Zhu

NeurIPS 2024 Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff Jian Qian, Haichen Hu, David Simchi-Levi

ICML 2024 Privacy Preserving Adaptive Experiment Design Jiachun Li, Kaining Shi, David Simchi-Levi

AISTATS 2023 Multi-Armed Bandit Experimental Design: Online Decision-Making and Adaptive Inference David Simchi-Levi, Chonghuan Wang

NeurIPS 2023 Non-Stationary Experimental Design Under Linear Trends David Simchi-Levi, Chonghuan Wang, Zeyu Zheng

ICML 2023 Pricing Experimental Design: Causal Effect, Expected Revenue and Tail Risk David Simchi-Levi, Chonghuan Wang

NeurIPS 2023 Stochastic Multi-Armed Bandits: Optimal Trade-Off Among Optimality, Consistency, and Tail Risk David Simchi-Levi, Zeyu Zheng, Feng Zhu

AISTATS 2022 Sobolev Norm Learning Rates for Conditional Mean Embeddings Prem Talwai, Ali Shameli, David Simchi-Levi

NeurIPS 2022 A Simple and Optimal Policy Design for Online Learning with Safety Against Heavy-Tailed Risk David Simchi-Levi, Zeyu Zheng, Feng Zhu

NeurIPS 2022 Context-Based Dynamic Pricing with Partially Linear Demand Model Jinzhi Bu, David Simchi-Levi, Chonghuan Wang

NeurIPS 2022 Learning Mixed Multinomial Logits with Provable Guarantees Yiqun Hu, David Simchi-Levi, Zhenzhen Yan

COLT 2022 Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation Dylan J Foster, Akshay Krishnamurthy, David Simchi-Levi, Yunzong Xu

AISTATS 2021 Reaping the Benefits of Bundling Under High Production Costs Will Ma, David Simchi-Levi

ICML 2021 Dynamic Planning and Learning Under Recovering Rewards David Simchi-Levi, Zeyu Zheng, Feng Zhu

COLT 2021 Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective Dylan Foster, Alexander Rakhlin, David Simchi-Levi, Yunzong Xu

ICML 2021 Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar

ICML 2020 Online Pricing with Offline Data: Phase Transition and Inverse Square Law Jinzhi Bu, David Simchi-Levi, Yunzong Xu

ICML 2020 Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu

AISTATS 2019 Learning to Optimize Under Non-Stationarity Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu

NeurIPS 2019 Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints David Simchi-Levi, Yunzong Xu

NeurIPS 2018 The Lingering of Gradients: How to Reuse Gradients over Time Zeyuan Allen-Zhu, David Simchi-Levi, Xinshang Wang