22 citations · 109 across the 34 of their papers we have counts for
6 papers · 1 filter
Optimal Computing Budget Allocation for Data-driven Ranking and Selection
Yuhao Wang, Enlu Zhou
In a fixed budget ranking and Selection (R&S) problem, one aims to identify the best design among a finite number of candidates by efficiently allocating the given computing budget…
Risk-averse Contextual Multi-armed Bandit Problem with Linear Payoffs
Yifan Lin, Yuhao Wang, Enlu Zhou
In this paper we consider the contextual multi-armed bandit problem for linear payoffs under a risk-averse criterion. At each round, contexts are revealed for each arm, and the dec…
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably
Tianyi Liu, Yan Li, Enlu Zhou +1
We investigate the role of noise in optimization algorithms for learning over-parameterized models. Specifically, we consider the recovery of a rank one matrix $Y^*\in R^{d\times d…
Bayesian Stochastic Gradient Descent for Stochastic Optimization with Streaming Input Data
Tianyi Liu, Yifan Lin, Enlu Zhou
We consider stochastic optimization under distributional uncertainty, where the unknown distributional parameter is estimated from streaming data that arrive sequentially over time…
Robust Multi-Objective Bayesian Optimization Under Input Noise
Samuel Daulton, Sait Cakmak, Maximilian Balandat +3
Bayesian optimization (BO) is a sample-efficient approach for tuning design parameters to optimize expensive-to-evaluate, black-box performance metrics. In many manufacturing proce…
Contextual Ranking and Selection with Gaussian Processes
Sait Cakmak, Siyang Gao, Enlu Zhou
In many real world problems, we are faced with the problem of selecting the best among a finite number of alternatives, where the best alternative is determined based on context sp…