01이 칸의 논문
- Learning Optimal Prescriptive Trees from Observational Data
- A Nonparametric Framework for Online Stochastic Matching with Correlated Arrivals
- Nonstationary Experimental Design Under Structured Trends
- Speed Up the Cold-Start Learning in Two-Sided Bandits with Many Arms
- Learning to Optimally Stop Diffusion Processes, with Financial Applications
- Transfer Learning, Cross Learning and Co-Learning with Operational Data Analytics (ODA)
- Markovian Search with Ex Ante Constraints: Theory and Applications to Socially Aware Algorithmic Hiring
- Fast and Simple Adaptive Elicitations
- Using Neural Networks to Guide Data-Driven Operational Decisions
- Learning to Cover: Online Learning and Optimization with Irreversible Decisions
- Predictive Production-and-Service Planning: Ambiguity Aversion with Performance Guarantees
- Robust Optimization with Decision-Dependent Information Discovery
- Online Stochastic Optimization with Wasserstein-Based Nonstationarity
- Contextual Learning with Online Convex Optimization: Theory and Application to Medical Decision-Making
- On Generalization and Regularization via Wasserstein Distributionally Robust Optimization
- On the Optimality of Affine Decision Rules in Distributionally Robust Optimization
- The Benefits of Delay to Online Decision Making
- Relaxed Indexability and Index Policy for Partially Observable Restless Bandits
- Beyond IID: Data-Driven Decision Making in Heterogeneous Environments
- A Sample Size Calculation for Training and Certifying Targeting Policies
- Adaptive Data Acquisition for Personalized Recommendations with Optimality Guarantees on Short-Form Video Platforms
- Toward a Liquid Biopsy: Greedy Approximation Algorithms for Active Sequential Hypothesis Testing
- Efficient Switchback Experiments with Surrogate Variables: Estimation and Experimental Design
- Learning Personalized Treatment Strategies with Predictive and Prognostic Covariates in Adaptive Clinical Trials
- A Framework for Selecting Action Portfolios with Incomplete and Action-Dependent Scenario Probabilities
- Algorithmic Precision and Human Decision: A Study of Interactive Optimization for School Schedules
- Data-Pooling Reinforcement Learning for Preventative Healthcare Intervention
- On the Impossibility of Statistically Improving Empirical Optimization: A Second Order Stochastic Dominance Perspective
- Optimal Decision Making Under Strategic Behavior
- Online Advertisement Allocation Under Customer Choices and Algorithmic Fairness
02같은 주제, 다른 방법
- Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Panel Experiments
- Estimation Errors as Regret Lower Bounds for Linear Contextual Bandits
- EnsembleIV: Creating Instrumental Variables from Ensemble Learners for Robust Statistical Inference with ML- Generated Variables
- T ail -GAN: Learning to Simulate Tail Risk Scenarios
- Multitask Learning and Bandits via Robust Statistics
- A Method for Asynchronous Time Series Analysis with Marketing Applications
- Getting the Most Out of A/B Tests Using the Asymptotic Minimax-Regret Criteria
- Last-Iterate Convergence in No-Regret Learning: Games with Reference Effects Under Logit Demand
- Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information
- Deferred Acceptance with News Utility