56 citations · 110 across the 16 of their papers we have counts for
5 papers · 1 filter
Regret Bounds and Experimental Design for Estimate-then-Optimize
Samuel Tan, Peter I. Frazier
In practical applications, data is used to make decisions in two steps: estimation and optimization. First, a machine learning model estimates parameters for a structural model rel…
Dynamic Pricing Provides Robust Equilibria in Stochastic Ridesharing Networks
J. Massey Cashore, Peter I. Frazier, Eva Tardos
Ridesharing markets are complex: drivers are strategic, rider demand and driver availability are stochastic, and complex city-scale phenomena like weather induce large scale correl…
Restless Bandits with Many Arms: Beating the Central Limit Theorem
Xiangyu Zhang, Peter I. Frazier
We consider finite-horizon restless bandits with multiple pulls per period, which play an important role in recommender systems, active learning, revenue management, and many other…
An Asymptotically Optimal Index Policy for Finite-Horizon Restless Bandits
Weici Hu, Peter Frazier
We consider restless multi-armed bandit (RMAB) with a finite horizon and multiple pulls per period. Leveraging the Lagrangian relaxation, we approximate the problem with a collecti…
Multi-Step Bayesian Optimization for One-Dimensional Feasibility Determination
J. Massey Cashore, Lemuel Kumarga, Peter I. Frazier
Bayesian optimization methods allocate limited sampling budgets to maximize expensive-to-evaluate functions. One-step-lookahead policies are often used, but computing optimal multi…