2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Stochastic Approximation Methods for Distortion Risk Measure Optimization
Jinyang Jiang, Bernd Heidergott, Jiaqiao Hu +1
Distortion Risk Measures (DRMs) capture risk preferences in decision-making and serve as general criteria for managing uncertainty. This paper proposes gradient descent algorithms…
math.OC2023★ 2 cited
Quantile Optimization via Multiple Timescale Local Search for Black-box Functions
Jiaqiao Hu, Meichen Song, Michael C. Fu
We consider quantile optimization of black-box functions that are estimated with noise. We propose two new iterative three-timescale local search algorithms. The first algorithm us…
cs.LG2023★ 1 cited
Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms
Jinyang Jiang, Jiaqiao Hu, Yijie Peng
Classical reinforcement learning (RL) aims to optimize the expected cumulative reward. In this work, we consider the RL setting where the goal is to optimize the quantile of the cu…