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20092024
most citedA Tutorial on Bayesian Optimization

363 citations · 1.1k across the 50 of their papers we have counts for

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7 papers · 1 filter

math.OC2022

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…

math.OC2022

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…

math.OC2021★ 9 cited

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…

math.OC2017★ 5 cited

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…

math.OC2016★ 2 cited

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…

math.OC2014

A New Optimal Stepsize For Approximate Dynamic Programming

Ilya O. Ryzhov, Peter I. Frazier, Warren B. Powell

Approximate dynamic programming (ADP) has proven itself in a wide range of applications spanning large-scale transportation problems, health care, revenue management, and energy sy…

math.OC2014★ 3 cited

Exploration vs. Exploitation in the Information Filtering Problem

Xiaoting Zhao, Peter I. Frazier

We consider information filtering, in which we face a stream of items too voluminous to process by hand (e.g., scientific articles, blog posts, emails), and must rely on a computer…