Found 46 results
Filters: Keyword is a. Statistical Learning in Operations and Author is David Simchi-Levi [Clear All Filters]
Robust Stochastic Lot-Sizing by Means of Histograms. Production and Operations Management. 22. 2013.
Analytics for an Online Retailer: Demand Forecasting and Price Optimization. Manufacturing and Service Operations Management. 18(1). 2016.
Dynamic Pricing and Demand Learning with Limited Price Experimentation. Operations Research. 65(6). 2017.
Uplift Modeling with Multiple Treatments and General Response Types. SIAM Data Mining 2017.. 2017.
The Lingering of Gradients: How to Reuse Gradients Over Time. NeurIPS 2018. (31). 2018.
Online Network Revenue Management using Thompson Sampling. Operations Research. 66(6). 2018.
Algorithms for Online Matching, Assortment, and Pricing with Tight Weight-Dependent Competitive Ratios. Operations Research.. 2019.
Dynamic Learning and Pricing with Model Misspecification. Management Science.. 2019.
Learning to Optimize under Non-Stationarity. AISTATS 2019.. 2019.
Sampling-based Approximation Schemes for Capacitated Stochastic Inventory Control Models. Mathematics of Operations Research.. 2019.
Dynamic Pricing (and Assortment) under a Static Calendar. Management Science.. 2020.
Hedging the Drift: Learning to Optimize under Non-Stationarity. Management Science—Special Issue on Data-Driven Prescriptive Analytics.. 2020.
Multi-Modal Dynamic Pricing. Management Science.. 2020.
Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses. Management Science.. 2020.
A Statistical Learning Approach to Personalization in Revenue Management. Management Science.. 2020.
Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits under Realizability. Mathematics of Operations Research.. 2021.
Data-Driven Approximation Schemes for Joint Pricing and Inventory Control Models. Management Science.. 2021.
Distributionally Robust Linear and Discrete Optimization with Marginals. Operations Research.. 2021.
Dynamic Pricing and Inventory Control with Fixed Ordering Cost and Incomplete Demand Information. Management Science.. 2021.
Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective. COLT 2021.. 2021.
Inventory Balancing with Online Learning. Management Science.. 2021.
Offline Pricing and Demand Learning with Censored Data. Management Science.. 2021.
Online Learning and Optimization for Revenue Management Problems with Add-on Discounts. Management Science.. 2021.
Online Pricing with Offline Data: Phase Transition and Inverse Square Law. Management Science.. 2021.
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning. Management Science.. 2021.
Bandits atop Reinforcement Learning: Tackling Online Inventory Models with Cyclic Demands. Management Science.. 2022.
Calibrating Sales Forecast in a Pandemic Using Competitive Online Non-Parametric Regression. Management Science.. 2022.
Design and Analysis of Switchback Experiments. Management Science.. 2022.
Estimating and Exploiting the Impact of Photo Layout: A Structural Approach. Management Science.. 2022.
Learning Mixed Multinomial Logits with Provable Guarantees. NeurIPS 2022.. 2022.
Phase Transitions in Bandits with Switching Constraints. Management Science.. 2022.
A Simple and Optimal Policy Design with Safety against Heavy-tailed Risk for Multi-armed Bandits. NeurIPS 2022.. 2022.
Assortment Planning for Recommendations at Checkout under Inventory Constraints. Mathematics of Operations Research.. 2023.
Non-Stationary Reinforcement Learning: The Blessing of (More) Optimism. Management Science.. 2023.
Offline Planning and Online Learning under Recovering Rewards. Management Science.. 2023.
Online Matching with Bayesian Rewards. Operations Research.. 2023.
Stochastic Multi-armed Bandits: Optimal Trade-off among Optimality, Consistency, and Tail Risk. NeurIPS 2023 Spotlight (top 3%).. 2023.