01이 칸의 논문
- A Nonparametric Framework for Online Stochastic Matching with Correlated Arrivals
- Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Panel Experiments
- Fast and Simple Adaptive Elicitations
- A Method for Asynchronous Time Series Analysis with Marketing Applications
- Getting the Most Out of A/B Tests Using the Asymptotic Minimax-Regret Criteria
- Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information
- Leveraging Expert Consistency to Improve Algorithmic Decision Support
- “Small Data”: Inference with Occasionally Observed States
- The (Surprising) Sample Optimality of Greedy Procedures for Large-Scale Ranking and Selection
- Pigeonhole Design: Balancing Sequential Experiments from an Online Matching Perspective
- A Simple and Optimal Policy Design with Safety Against Heavy-Tailed Risk for Stochastic Bandits
- Online Learning and Decision Making Under Generalized Linear Model with High-Dimensional Data
- Artificial Intelligence: Can Seemingly Collusive Outcomes Be Avoided?
- Ambiguous Dynamic Treatment Regimes: A Reinforcement Learning Approach
- A Heuristic Approach to Explore: The Value of Perfect Information
- Design and Analysis of Switchback Experiments
- Deep Reinforcement Learning for Sequential Targeting
- Balancing Optimal Large Deviations in Sequential Selection
- An Asymptotically Tight Learning Algorithm for Mobile-Promotion Platforms
- Random Projection Estimation of Discrete-Choice Models with Large Choice Sets
02같은 주제, 다른 방법
- Learning Optimal Prescriptive Trees from Observational Data
- 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)
- Estimation Errors as Regret Lower Bounds for Linear Contextual Bandits
- Markovian Search with Ex Ante Constraints: Theory and Applications to Socially Aware Algorithmic Hiring
- Using Neural Networks to Guide Data-Driven Operational Decisions
- EnsembleIV: Creating Instrumental Variables from Ensemble Learners for Robust Statistical Inference with ML- Generated Variables
- Learning to Cover: Online Learning and Optimization with Irreversible Decisions