1.2k citations · 2.1k across the 35 of their papers we have counts for
10 papers · 1 filter
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations
Wenlei Shi, Xinran Wei, Jia Zhang +4
Multi-agent reinforcement learning (MARL) has been increasingly explored to learn the cooperative policy towards maximizing a certain global reward. Many existing studies take adva…
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu +1
Stock trend forecasting has become a popular research direction that attracts widespread attention in the financial field. Though deep learning methods have achieved promising resu…
COSEA: Convolutional Code Search with Layer-wise Attention
Hao Wang, Jia Zhang, Yingce Xia +3
Semantic code search, which aims to retrieve code snippets relevant to a given natural language query, has attracted many research efforts with the purpose of accelerating software…
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler
Zhining Liu, Pengfei Wei, Jing Jiang +3
Imbalanced learning (IL), i.e., learning unbiased models from class-imbalanced data, is a challenging problem. Typical IL methods including resampling and reweighting were designed…
Qlib: An AI-oriented Quantitative Investment Platform
Xiao Yang, Weiqing Liu, Dong Zhou +2
Quantitative investment aims to maximize the return and minimize the risk in a sequential trading period over a set of financial instruments. Recently, inspired by rapid developmen…
Learning to Reweight with Deep Interactions
Yang Fan, Yingce Xia, Lijun Wu +5
Recently, the concept of teaching has been introduced into machine learning, in which a teacher model is used to guide the training of a student model (which will be used in real t…
Measuring Model Complexity of Neural Networks with Curve Activation Functions
Xia Hu, Weiqing Liu, Jiang Bian +1
It is fundamental to measure model complexity of deep neural networks. The existing literature on model complexity mainly focuses on neural networks with piecewise linear activatio…
MC-BERT: Efficient Language Pre-Training via a Meta Controller
Zhenhui Xu, Linyuan Gong, Guolin Ke +5
Pre-trained contextual representations (e.g., BERT) have become the foundation to achieve state-of-the-art results on many NLP tasks. However, large-scale pre-training is computati…
Invertible Image Rescaling
Mingqing Xiao, Shuxin Zheng, Chang Liu +6
High-resolution digital images are usually downscaled to fit various display screens or save the cost of storage and bandwidth, meanwhile the post-upscaling is adpoted to recover t…
Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction
Chi Chen, Li Zhao, Wei Cao +2
Nowadays, machine learning methods have been widely used in stock prediction. Traditional approaches assume an identical data distribution, under which a learned model on the train…