Selected Publications

Found 46 results
Filters: Keyword is a. Statistical Learning in Operations and Author is David Simchi-Levi  [Clear All Filters]
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a. Statistical Learning in Operations
Cheung W.C, Simchi-Levi D, Zhu R.  2020.  Hedging the Drift: Learning to Optimize under Non-Stationarity. Management Science—Special Issue on Data-Driven Prescriptive Analytics.
Wang Y, Chen B, Simchi-Levi D.  2020.  Multi-Modal Dynamic Pricing. Management Science.
Jin R, Simchi-Levi D, Wang L, Wang X, Yang S.  2020.  Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses. Management Science.
Chen X, Owen Z, Pixton C, Simchi-Levi D.  2020.  A Statistical Learning Approach to Personalization in Revenue Management. Management Science.
Ma W, Simchi-Levi D, Zhao J.  2020.  Dynamic Pricing (and Assortment) under a Static Calendar. Management Science.
Bu J, Simchi-Levi D, Xu Y.  2020.  Online Pricing with Offline Data: Phase Transition and Inverse Square Law. ICML 2020.
Cheung W.C, Simchi-Levi D, Zhu R.  2019.  Learning to Optimize under Non-Stationarity. AISTATS 2019.
Cheung W.C, Simchi-Levi D.  2019.  Sampling-based Approximation Schemes for Capacitated Stochastic Inventory Control Models. Mathematics of Operations Research.
Ma W, Simchi-Levi D.  2019.  Algorithms for Online Matching, Assortment, and Pricing with Tight Weight-Dependent Competitive Ratios. Operations Research.
Simchi-Levi D, Xu Y.  2019.  Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints. NeurIPS 2019.
Nambiar M, Simchi-Levi D, Wang H.  2019.  Dynamic Learning and Pricing with Model Misspecification. Management Science.
Ferreira J.K, Simchi-Levi D, Wang H.  2018.  Online Network Revenue Management using Thompson Sampling. Operations Research. 66(6)
Allen-Zhu Z, Simchi-Levi D, Wang X.  2018.  The Lingering of Gradients: How to Reuse Gradients Over Time. NeurIPS 2018. (31)
Zhao Y, Fang X, Simchi-Levi D.  2017.  Uplift Modeling with Multiple Treatments and General Response Types. SIAM Data Mining 2017.
Cheung W.C, Simchi-Levi D, Wang H.  2017.  Dynamic Pricing and Demand Learning with Limited Price Experimentation. Operations Research. 65(6)
Ferreira J.K, Lee A.BH, Simchi-Levi D.  2016.  Analytics for an Online Retailer: Demand Forecasting and Price Optimization. Manufacturing and Service Operations Management. 18(1)
Klabjan D, Simchi-Levi D, Song M.  2013.  Robust Stochastic Lot-Sizing by Means of Histograms. Production and Operations Management. 22
Chen X, Simchi-Levi D, Wang Y.  2021.  Privacy-Preserving Dynamic Personalized Pricing with Demand Learning. Management Science.
Foster D, Rakhlin A, Simchi-Levi D, Xu Y.  2021.  Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective. COLT 2021.
Mao W, Zhang K, Zhu R, Simchi-Levi D, Basar T.  2021.  Is Model-Free Learning Nearly Optimal for Non-Stationary RL? ICML 2021.
Simchi-Levi D, Zheng Z, Zhu F.  2021.  Dynamic Planning and Learning under Recovering Rewards. ICML 2021.
Simchi-Levi D, Xu Y.  2021.  Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits under Realizability. Mathematics of Operations Research.
Qin H, Simchi-Levi D, Wang L.  2021.  Data-Driven Approximation Schemes for Joint Pricing and Inventory Control Models. Management Science.
Chen B, Simchi-Levi D, Wang Y, Zhou Y.  2021.  Dynamic Pricing and Inventory Control with Fixed Ordering Cost and Incomplete Demand Information. Management Science.
Simchi-Levi D, Sun R, Zhang H.  2021.  Online Learning and Optimization for Revenue Management Problems with Add-on Discounts. Management Science.
Cheung W.C, Ma W, Simchi-Levi D, Wang X.  2021.  Inventory Balancing with Online Learning. Management Science.
Bu J, Simchi-Levi D, Xu Y.  2021.  Online Pricing with Offline Data: Phase Transition and Inverse Square Law. Management Science.
Chen L, Ma W, Natarajan K, Simchi-Levi D, Yan Z.  2021.  Distributionally Robust Linear and Discrete Optimization with Marginals. Operations Research.
Bu J, Simchi-Levi D, Wang L.  2021.  Offline Pricing and Demand Learning with Censored Data. Management Science.
Talwai P, Shameli A, Simchi-Levi D.  2022.  Sobolev Norm Learning Rates for Conditional Mean Embeddings. AISTAT 2022.
Bojinov I, Simchi-Levi D, Zhao J.  2022.  Design and Analysis of Switchback Experiments. Management Science.
Li H, Simchi-Levi D, Wu M, Zhu W.  2022.  Estimating and Exploiting the Impact of Photo Layout: A Structural Approach. Management Science.
Foster D, Krishnamurthy A, Simchi-Levi D, Xu Y.  2022.  Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation. COLT 2022.
Simchi-Levi D, Xu Y.  2022.  Phase Transitions in Bandits with Switching Constraints. Management Science.
Simchi-Levi D, Sun R, Wu MXiao, Zhu R.  2022.  Calibrating Sales Forecast in a Pandemic Using Competitive Online Non-Parametric Regression. Management Science.
Gong X, Simchi-Levi D.  2022.  Bandits atop Reinforcement Learning: Tackling Online Inventory Models with Cyclic Demands. Management Science.
Simchi-Levi D, Zheng Z, Zhu F.  2022.  A Simple and Optimal Policy Design with Safety against Heavy-tailed Risk for Multi-armed Bandits. NeurIPS 2022.
Hu Y, Simchi-Levi D, Yan Z.  2022.  Learning Mixed Multinomial Logits with Provable Guarantees. NeurIPS 2022.
Bu J, Simchi-Levi D, Wang C.  2022.  Context-Based Dynamic Pricing with Partially Linear Demand Model. NeurIPS 2022.
Ma W, Simchi-Levi D.  2022.  Constructing Demand Curves from a Single Observation of Bundle Sales. WINE 2022.
Chen X, Ma W, Simchi-Levi D, Xin L.  2023.  Assortment Planning for Recommendations at Checkout under Inventory Constraints. Mathematics of Operations Research.
Cheung W. C., Simchi-Levi D, Zhu R.  2023.  Non-Stationary Reinforcement Learning: The Blessing of (More) Optimism. Management Science.
Simchi-Levi D, Sun R, Wang X.  2023.  Online Matching with Bayesian Rewards. Operations Research.
Simchi-Levi D, Zheng Z, Zhu F.  2023.  Offline Planning and Online Learning under Recovering Rewards. Management Science.
Simchi-Levi D, Wang C, Zheng Z.  2023.  Non-stationary Experimental Design under Linear Trends. NeurIPS.
Zhu F, Zheng Z, Simchi-Levi D.  2023.  Stochastic Multi-armed Bandits: Optimal Trade-off among Optimality, Consistency, and Tail Risk. NeurIPS 2023 Spotlight (top 3%).