12 citations · 27 across the 6 of their papers we have counts for
6 papers
Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy
Hongyang Yang, Xiao-Yang Liu, Shan Zhong +1
Stock trading strategies play a critical role in investment. However, it is challenging to design a profitable strategy in a complex and dynamic stock market. In this paper, we pro…
FinGPT-HPC: Efficient Pretraining and Finetuning Large Language Models for Financial Applications with High-Performance Computing
Xiao-Yang Liu, Jie Zhang, Guoxuan Wang +2
Large language models (LLMs) are computationally intensive. The computation workload and the memory footprint grow quadratically with the dimension (layer width). Most of LLMs' par…
Deep Reinforcement Learning for Traffic Light Control in Intelligent Transportation Systems
Ming Zhu, Xiao-Yang Liu, Sem Borst +1
Smart traffic lights in intelligent transportation systems (ITSs) are envisioned to greatly increase traffic efficiency and reduce congestion. Deep reinforcement learning (DRL) is…
Regenerative Particle Thompson Sampling
Zeyu Zhou, Bruce Hajek, Nakjung Choi +1
This paper proposes regenerative particle Thompson sampling (RPTS), a flexible variation of Thompson sampling. Thompson sampling itself is a Bayesian heuristic for solving stochast…
ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning
Xiao-Yang Liu, Zechu Li, Zhuoran Yang +5
Deep reinforcement learning (DRL) has revolutionized learning and actuation in applications such as game playing and robotic control. The cost of data collection, i.e., generating…
Network Protection Design Using Network Coding
Salah A. Aly, Ahmed E. Kamal, Anwar I. Walid
Link and node failures are two common fundamental problems that affect operational networks. Protection of communication networks against such failures is essential for maintaining…