47 citations · 99 across the 9 of their papers we have counts for
11 papers
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo +5
It is challenging for reinforcement learning (RL) algorithms to succeed in real-world applications like financial trading and logistic system due to the noisy observation and envir…
Instance-wise Graph-based Framework for Multivariate Time Series Forecasting
Wentao Xu, Weiqing Liu, Jiang Bian +2
The multivariate time series forecasting has attracted more and more attention because of its vital role in different fields in the real world, such as finance, traffic, and weathe…
Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu +1
Modeling and managing portfolio risk is perhaps the most important step to achieve growing and preserving investment performance. Within the modern portfolio construction framework…
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu +1
Successful quantitative investment usually relies on precise predictions of the future movement of the stock price. Recently, machine learning based solutions have shown their capa…
Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu +5
As a fundamental problem in algorithmic trading, order execution aims at fulfilling a specific trading order, either liquidation or acquirement, for a given instrument. Towards eff…
Model Complexity of Deep Learning: A Survey
Xia Hu, Lingyang Chu, Jian Pei +2
Model complexity is a fundamental problem in deep learning. In this paper we conduct a systematic overview of the latest studies on model complexity in deep learning. Model complex…