activity
20172021
most citedSparse online relative similarity learning

7 citations · 9 across the 9 of their papers we have counts for

collaborators

13 papers

cs.SI2021

Multi-Stage Network Embedding for Exploring Heterogeneous Edges

Hong Huang, Yu Song, Fanghua Ye +3

The relationships between objects in a network are typically diverse and complex, leading to the heterogeneous edges with different semantic information. In this paper, we focus on…

cs.CR2021

HomDroid: Detecting Android Covert Malware by Social-Network Homophily Analysis

Yueming Wu, Deqing Zou, Wei Yang +2

Android has become the most popular mobile operating system. Correspondingly, an increasing number of Android malware has been developed and spread to steal users' private informat…

cs.CL20211 cited

Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction

Zhexue Chen, Hong Huang, Bang Liu +2

Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from sentences, where each triplet includes an entity, its associated sentiment, and the opinion span explaining…

cs.LG20217 cited

Sparse online relative similarity learning

Dezhong Yao, Peilin Zhao, Chen Yu +2

For many data mining and machine learning tasks, the quality of a similarity measure is the key for their performance. To automatically find a good similarity measure from datasets…

cs.SI2021

Modeling Heterogeneous Edges to Represent Networks with Graph Auto-Encoder

Lu Wang, Yu Song, Hong Huang +3

In the real world, networks often contain multiple relationships among nodes, manifested as the heterogeneity of the edges in the networks. We convert the heterogeneous networks in…

cs.DC20191 cited

A Survey on Graph Processing Accelerators: Challenges and Opportunities

Chuangyi Gui, Long Zheng, Bingsheng He +4

Graph is a well known data structure to represent the associated relationships in a variety of applications, e.g., data science and machine learning. Despite a wealth of existing e…