1.2k citations · 1.5k across the 17 of their papers we have counts for
13 papers · 1 filter
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…
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…
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…
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…
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…