3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2023
From Bandits Model to Deep Deterministic Policy Gradient, Reinforcement Learning with Contextual Information
Zhendong Shi, Xiaoli Wei, Ercan E. Kuruoglu
The problem of how to take the right actions to make profits in sequential process continues to be difficult due to the quick dynamics and a significant amount of uncertainty in ma…
q-fin.TR2023★ 3 cited
Optimizing Trading Strategies in Quantitative Markets using Multi-Agent Reinforcement Learning
Hengxi Zhang, Zhendong Shi, Yuanquan Hu +3
Quantitative markets are characterized by swift dynamics and abundant uncertainties, making the pursuit of profit-driven stock trading actions inherently challenging. Within this c…
stat.ML2022
Thompson Sampling on Asymmetric -Stable Bandits
Zhendong Shi, Ercan E. Kuruoglu, Xiaoli Wei
In algorithm optimization in reinforcement learning, how to deal with the exploration-exploitation dilemma is particularly important. Multi-armed bandit problem can optimize the pr…