39 citations · 42 across the 6 of their papers we have counts for
6 papers
InvariantStock: Learning Invariant Features for Mastering the Shifting Market
Haiyao Cao, Jinan Zou, Yuhang Liu +4
Accurately predicting stock returns is crucial for effective portfolio management. However, existing methods often overlook a fundamental issue in the market, namely, distribution…
Rethinking State Disentanglement in Causal Reinforcement Learning
Haiyao Cao, Zhen Zhang, Panpan Cai +7
One of the significant challenges in reinforcement learning (RL) when dealing with noise is estimating latent states from observations. Causality provides rigorous theoretical supp…
Semantic Role Labeling Guided Out-of-distribution Detection
Jinan Zou, Maihao Guo, Yu Tian +5
Identifying unexpected domain-shifted instances in natural language processing is crucial in real-world applications. Previous works identify the out-of-distribution (OOD) instance…
Revisiting Image Reconstruction for Semi-supervised Semantic Segmentation
Yuhao Lin, Haiming Xu, Lingqiao Liu +2
Autoencoding, which aims to reconstruct the input images through a bottleneck latent representation, is one of the classic feature representation learning strategies. It has been s…
Stock Market Prediction via Deep Learning Techniques: A Survey
Jinan Zou, Qingying Zhao, Yang Jiao +6
Existing surveys on stock market prediction often focus on traditional machine learning methods instead of deep learning methods. This motivates us to provide a structured and comp…
Astock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing Model
Jinan Zou, Haiyao Cao, Lingqiao Liu +3
Natural Language Processing(NLP) demonstrates a great potential to support financial decision-making by analyzing the text from social media or news outlets. In this work, we build…