activity
20162020
most citedFew-Shot Knowledge Graph Completion

6 citations · 6 across the 2 of their papers we have counts for

collaborators

7 papers

cs.IR2020

Addressing Class-Imbalance Problem in Personalized Ranking

Lu Yu, Shichao Pei, Chuxu Zhang +4

Pairwise ranking models have been widely used to address recommendation problems. The basic idea is to learn the rank of users' preferred items through separating items into \emph{…

cs.LG2020

Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning

Mandana Saebi, Steven Krieg, Chuxu Zhang +2

Path-based relational reasoning over knowledge graphs has become increasingly popular due to a variety of downstream applications such as question answering in dialogue systems, fa…

cs.CL20196 cited

Few-Shot Knowledge Graph Completion

Chuxu Zhang, Huaxiu Yao, Chao Huang +3

Knowledge graphs (KGs) serve as useful resources for various natural language processing applications. Previous KG completion approaches require a large number of training instance…

cs.LG2019

Graph Few-shot Learning via Knowledge Transfer

Huaxiu Yao, Chuxu Zhang, Ying Wei +5

Towards the challenging problem of semi-supervised node classification, there have been extensive studies. As a frontier, Graph Neural Networks (GNNs) have aroused great interest r…

cs.LG2018

A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data

Chuxu Zhang, Dongjin Song, Yuncong Chen +7

Nowadays, multivariate time series data are increasingly collected in various real world systems, e.g., power plants, wearable devices, etc. Anomaly detection and diagnosis in mult…

cs.SI2018

CARL: Content-Aware Representation Learning for Heterogeneous Networks

Chuxu Zhang, Ananthram Swami, Nitesh V. Chawla

Heterogeneous networks not only present a challenge of heterogeneity in the types of nodes and relations, but also the attributes and content associated with the nodes. While recen…