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20192023
most citedOn the Finite-Time Performance of the Knowledge Gradient Algorithm

3 citations · 11 across the 8 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

stat.ML2022★ 1 cited

Convergence Rate Analysis for Optimal Computing Budget Allocation Algorithms

Yanwen Li, Siyang Gao

Ordinal optimization (OO) is a widely-studied technique for optimizing discrete-event dynamic systems (DEDS). It evaluates the performance of the system designs in a finite set by…

stat.ML2022

Asymptotic Optimality of Myopic Ranking and Selection Procedures

Yanwen Li, Siyang Gao, Zhongshun Shi

Ranking and selection (R&S) is a popular model for studying discrete-event dynamic systems. It aims to select the best design (the design with the largest mean performance) from a…

stat.ME2022★ 1 cited

Convergence Analysis of Stochastic Kriging-Assisted Simulation with Random Covariates

Cheng Li, Siyang Gao, Jianzhong Du

We consider performing simulation experiments in the presence of covariates. Here, covariates refer to some input information other than system designs to the simulation model that…

math.OC2022★ 3 cited

A Contextual Ranking and Selection Method for Personalized Medicine

Jianzhong Du, Siyang Gao, Chun-Hung Chen

Problem definition: Personalized medicine (PM) seeks the best treatment for each patient among a set of available treatment methods. Since a specific treatment does not work well o…

stat.ML2022★ 3 cited

On the Finite-Time Performance of the Knowledge Gradient Algorithm

Yanwen Li, Siyang Gao

The knowledge gradient (KG) algorithm is a popular and effective algorithm for the best arm identification (BAI) problem. Due to the complex calculation of KG, theoretical analysis…

math.OC2022

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…