16 citations · 46 across the 34 of their papers we have counts for
10 papers · 1 filter
SceneSelect: Selective Learning for Trajectory Scene Classification and Expert Scheduling
Xinrun Wang, Deshun Xia, Yuxi Sun +1
Accurate trajectory prediction is fundamentally challenging due to high scene heterogeneity - the severe variance in motion velocity, spatial density, and interaction patterns acro…
FineFT: Efficient and Risk-Aware Ensemble Reinforcement Learning for Futures Trading
Molei Qin, Xinyu Cai, Yewen Li +5
Futures are contracts obligating the exchange of an asset at a predetermined date and price, notable for their high leverage and liquidity and, therefore, thrive in the Crypto mark…
Resolving Latency and Inventory Risk in Market Making with Reinforcement Learning
Junzhe Jiang, Chang Yang, Xinrun Wang +3
The latency of the exchanges in Market Making (MM) is inevitable due to hardware limitations, system processing times, delays in receiving data from exchanges, the time required fo…
Double Oracle Neural Architecture Search for Game Theoretic Deep Learning Models
Aye Phyu Phyu Aung, Xinrun Wang, Ruiyu Wang +4
In this paper, we propose a new approach to train deep learning models using game theory concepts including Generative Adversarial Networks (GANs) and Adversarial Training (AT) whe…
MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading
Chuqiao Zong, Chaojie Wang, Molei Qin +3
High-frequency trading (HFT) that executes algorithmic trading in short time scales, has recently occupied the majority of cryptocurrency market. Besides traditional quantitative t…
True Knowledge Comes from Practice: Aligning LLMs with Embodied Environments via Reinforcement Learning
Weihao Tan, Wentao Zhang, Shanqi Liu +3
Despite the impressive performance across numerous tasks, large language models (LLMs) often fail in solving simple decision-making tasks due to the misalignment of the knowledge i…