A Convex Programming Approach to Data-Driven Risk-Averse Reinforcement Learning

Reinforcement learning for linear exponential quadratic Gaussian problem

J Lai, J Xiong - Systems & Control Letters, 2024 - Elsevier
This paper addresses the infinite-horizon linear exponential quadratic Gaussian problem for
a class of stochastic systems with additive noise. A model-free generalized policy iteration …
被引用次数：1 相关文章
[PDF] researchgate.net

[PDF][PDF] Bidding via clustering ads intentions: an efficient search engine marketing system for ecommerce

C Jie, ZW Da Xu, L Wang, W Shen - 2nd International Workshop …, 2021 - researchgate.net
With the increasing scale of search engine marketing, designing an efficient bidding system
is becoming paramount for the success of e-commerce companies. The critical challenges …
被引用次数：14 相关文章 所有 2 个版本
[PDF] arxiv.org

An Efficient Group-based Search Engine Marketing System for E-Commerce

C Jie, D Xu, Z Wang, L Wang, W Shen - arXiv preprint arXiv:2106.12700, 2021 - arxiv.org
With the increasing scale of search engine marketing, designing an efficient bidding system
is becoming paramount for the success of e-commerce companies. The critical challenges …
被引用次数：3 相关文章 所有 3 个版本

A One-shot Convex Optimization Approach to Risk-Averse Q-Learning

Y Han, M Mazouchi, S Nageshrao… - 2021 60th IEEE …, 2021 - ieeexplore.ieee.org
This paper presents a model-free Q-learning algorithm for solving the risk-averse optimal
control (RAOC) problem. The entropic risk measure is used in the RAOC to account for the …
相关文章 所有 2 个版本