33 citations · 78 across the 11 of their papers we have counts for
11 papers
Imbalanced Node Classification Beyond Homophilic Assumption
Jie Liu, Mengting He, Guangtao Wang +3
Imbalanced node classification widely exists in real-world networks where graph neural networks (GNNs) are usually highly inclined to majority classes and suffer from severe perfor…
Model-Agnostic Decentralized Collaborative Learning for On-Device POI Recommendation
Jing Long, Tong Chen, Nguyen Quoc Viet Hung +3
As an indispensable personalized service in Location-based Social Networks (LBSNs), the next Point-of-Interest (POI) recommendation aims to help people discover attractive and inte…
Joint Multilingual Knowledge Graph Completion and Alignment
Vinh Tong, Dat Quoc Nguyen, Trung Thanh Huynh +3
Knowledge graph (KG) alignment and completion are usually treated as two independent tasks. While recent work has leveraged entity and relation alignments from multiple KGs, such a…
Efficient On-Device Session-Based Recommendation
Xin Xia, Junliang Yu, Qinyong Wang +3
On-device session-based recommendation systems have been achieving increasing attention on account of the low energy/resource consumption and privacy protection while providing pro…
XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation
Junliang Yu, Xin Xia, Tong Chen +3
Contrastive learning (CL) has recently been demonstrated critical in improving recommendation performance. The underlying principle of CL-based recommendation models is to ensure t…
CIRCLE: Continual Repair across Programming Languages
Wei Yuan, Quanjun Zhang, Tieke He +4
Automatic Program Repair (APR) aims at fixing buggy source code with less manual debugging efforts, which plays a vital role in improving software reliability and development produ…
On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation
Xin Xia, Hongzhi Yin, Junliang Yu +3
Modern recommender systems operate in a fully server-based fashion. To cater to millions of users, the frequent model maintaining and the high-speed processing for concurrent user…
PM-LSH: a fast and accurate in-memory framework for high-dimensional approximate NN and closest pair search
Bolong Zheng, Xi Zhao, Lianggui Weng +3
Nearest neighbor (NN) search is inherently computationally expensive in high-dimensional spaces due to the curse of dimensionality. As a well-known solution, locality-sensitive has…
Socially-Aware Self-Supervised Tri-Training for Recommendation
Junliang Yu, Hongzhi Yin, Min Gao +3
Self-supervised learning (SSL), which can automatically generate ground-truth samples from raw data, holds vast potential to improve recommender systems. Most existing SSL-based me…
Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation
Junliang Yu, Hongzhi Yin, Jundong Li +3
Social relations are often used to improve recommendation quality when user-item interaction data is sparse in recommender systems. Most existing social recommendation models explo…
Heterogeneous Hypergraph Embedding for Graph Classification
Xiangguo Sun, Hongzhi Yin, Bo Liu +4
Recently, graph neural networks have been widely used for network embedding because of their prominent performance in pairwise relationship learning. In the real world, a more natu…