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20162022
most citedUnbiased Simulation for Optimizing Stochastic Function Compositions

12 citations · 34 across the 11 of their papers we have counts for

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7 papers · 1 filter

math.OC20211 cited

Robust exploratory mean-variance problem with drift uncertainty

Chenchen Mou, Weiwei Zhang, Chao Zhou

We solve a min-max problem in a robust exploratory mean-variance problem with drift uncertainty in this paper. It is verified that robust investors choose the Sharpe ratio with min…

math.OC20206 cited

Mean Field Exponential Utility Game: A Probabilistic Approach

Guanxing Fu, Xizhi Su, Chao Zhou

We study an -player and a mean field exponential utility game. Each player manages two stocks; one is driven by an individual shock and the other is driven by a common shock. Mo…

math.OC2018

On Dynamic Programming Principle for Stochastic Control under Expectation Constraints

Yuk-Loong Chow, Xiang Yu, Chao Zhou

This paper studies the dynamic programming principle using the measurable selection method for stochastic control of continuous processes. The novelty of this work is to incorporat…

math.OC201712 cited

Unbiased Simulation for Optimizing Stochastic Function Compositions

Jose Blanchet, Donald Goldfarb, Garud Iyengar +2

In this paper, we introduce an unbiased gradient simulation algorithms for solving convex optimization problem with stochastic function compositions. We show that the unbiased grad…

math.OC2017

Using Negative Curvature in Solving Nonlinear Programs

Donald Goldfarb, Cun Mu, John Wright +1

Minimization methods that search along a curvilinear path composed of a non-ascent nega- tive curvature direction in addition to the direction of steepest descent, dating back to t…

math.OC20176 cited

Linear Convergence of Stochastic Frank Wolfe Variants

Donald Goldfarb, Garud Iyengar, Chaoxu Zhou

In this paper, we show that the Away-step Stochastic Frank-Wolfe Algorithm (ASFW) and Pairwise Stochastic Frank-Wolfe algorithm (PSFW) converge linearly in expectation. We also sho…