activity
20172024
most citedConnecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

117 citations · 724 across the 59 of their papers we have counts for

collaborators
Showing 2020Show all

16 papers · 1 filter

cs.LG2020★ 10 cited

SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning

Zhuowei Wang, Jing Jiang, Bo Han +4

Deep learning with noisy labels is a challenging task. Recent prominent methods that build on a specific sample selection (SS) strategy and a specific semi-supervised learning (SSL…

cs.CV2020★ 1 cited

Confusable Learning for Large-class Few-Shot Classification

Bingcong Li, Bo Han, Zhuowei Wang +2

Few-shot image classification is challenging due to the lack of ample samples in each class. Such a challenge becomes even tougher when the number of classes is very large, i.e., t…

cs.LG2020★ 3 cited

Cooperative Heterogeneous Deep Reinforcement Learning

Han Zheng, Pengfei Wei, Jing Jiang +3

Numerous deep reinforcement learning agents have been proposed, and each of them has its strengths and flaws. In this work, we present a Cooperative Heterogeneous Deep Reinforcemen…

cs.CL2020★ 3 cited

Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention

Yang Li, Tao Shen, Guodong Long +3

Wrong labeling problem and long-tail relations are two main challenges caused by distant supervision in relation extraction. Recent works alleviate the wrong labeling by selective…

cs.CL2020

RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion

Hao Huang, Guodong Long, Tao Shen +2

Many graph embedding approaches have been proposed for knowledge graph completion via link prediction. Among those, translating embedding approaches enjoy the advantages of light-w…

cs.LG2020

BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes

Xueping Peng, Guodong Long, Tao Shen +3

Electronic health records (EHRs) are longitudinal records of a patient's interactions with healthcare systems. A patient's EHR data is organized as a three-level hierarchy from top…