33 citations · 185 across the 30 of their papers we have counts for
33 papers
Online Resource Allocation with Average Budget Constraints
Ruicheng Ao, Hongyu Chen, David Simchi-Levi +1
We consider the problem of online resource allocation with average budget constraints. At each time point the decision maker makes an irrevocable decision of whether to accept or r…
Regret Distribution in Stochastic Bandits: Optimal Trade-off between Expectation and Tail Risk
David Simchi-Levi, Zeyu Zheng, Feng Zhu
We study the optimal trade-off between expectation and tail risk for regret distribution in the stochastic multi-armed bandit model. We fully characterize the interplay among three…
A Simple and Optimal Policy Design with Safety against Heavy-Tailed Risk for Stochastic Bandits
David Simchi-Levi, Zeyu Zheng, Feng Zhu
We study the stochastic multi-armed bandit problem and design new policies that enjoy both worst-case optimality for expected regret and light-tailed risk for regret distribution.…
Optimal Learning Rates for Regularized Least-Squares with a Fourier Capacity Condition
Prem Talwai, David Simchi-Levi
We derive minimax adaptive rates for a new, broad class of Tikhonov-regularized learning problems in Hilbert scales under general source conditions. Our analysis does not require t…
Dynamic Pricing and Demand Learning on a Large Network of Products: A PAC-Bayesian Approach
N. Bora Keskin, David Simchi-Levi, Prem Talwai
We consider a seller offering a large network of products over a time horizon of periods. The seller does not know the parameters of the products' linear demand model, and…
Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation
Dylan J. Foster, Akshay Krishnamurthy, David Simchi-Levi +1
We consider the offline reinforcement learning problem, where the aim is to learn a decision making policy from logged data. Offline RL -- particularly when coupled with (value) fu…