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20212025
most citedEfficient Non-Sampling Knowledge Graph Embedding

32 citations · 50 across the 11 of their papers we have counts for

collaborators

12 papers

cs.LG2025

Deep Cut-informed Graph Embedding and Clustering

Zhiyuan Ning, Zaitian Wang, Ran Zhang +8

Graph clustering aims to divide the graph into different clusters. The recently emerging deep graph clustering approaches are largely built on graph neural networks (GNN). However,…

cs.LG2024

Towards Graph Prompt Learning: A Survey and Beyond

Qingqing Long, Yuchen Yan, Peiyan Zhang +12

Large-scale "pre-train and prompt learning" paradigms have demonstrated remarkable adaptability, enabling broad applications across diverse domains such as question answering, imag…

cs.LG2024★ 2 cited

DisenSemi: Semi-supervised Graph Classification via Disentangled Representation Learning

Yifan Wang, Xiao Luo, Chong Chen +3

Graph classification is a critical task in numerous multimedia applications, where graphs are employed to represent diverse types of multimedia data, including images, videos, and…

cs.CV2024

DEMO: A Statistical Perspective for Efficient Image-Text Matching

Fan Zhang, Xian-Sheng Hua, Chong Chen +1

Image-text matching has been a long-standing problem, which seeks to connect vision and language through semantic understanding. Due to the capability to manage large-scale raw dat…

cs.LG2024★ 1 cited

Unveiling Delay Effects in Traffic Forecasting: A Perspective from Spatial-Temporal Delay Differential Equations

Qingqing Long, Zheng Fang, Chen Fang +3

Traffic flow forecasting is a fundamental research issue for transportation planning and management, which serves as a canonical and typical example of spatial-temporal predictions…

cs.CV2022

On Mitigating Hard Clusters for Face Clustering

Yingjie Chen, Huasong Zhong, Chong Chen +5

Face clustering is a promising way to scale up face recognition systems using large-scale unlabeled face images. It remains challenging to identify small or sparse face image clust…

cs.LG2021

Density-Based Clustering with Kernel Diffusion

Chao Zheng, Yingjie Chen, Chong Chen +2

Finding a suitable density function is essential for density-based clustering algorithms such as DBSCAN and DPC. A naive density corresponding to the indicator function of a unit $…

cs.IR2021★ 8 cited

ARGO: Modeling Heterogeneity in E-commerce Recommendation

Daqing Wu, Xiao Luo, Zeyu Ma +3

Nowadays, E-commerce is increasingly integrated into our daily lives. Meanwhile, shopping process has also changed incrementally from one behavior (purchase) to multiple behaviors…

cs.IR2021★ 3 cited

Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation

Xiao Luo, Daqing Wu, Yiyang Gu +7

Recent years have witnessed the explosive growth of interaction behaviors in multimedia information systems, where multi-behavior recommender systems have received increasing atten…

cs.CV2021★ 4 cited

Discriminative-Generative Dual Memory Video Anomaly Detection

Xin Guo, Zhongming Jin, Chong Chen +5

Recently, people tried to use a few anomalies for video anomaly detection (VAD) instead of only normal data during the training process. A side effect of data imbalance occurs when…

cs.CV2021

Graph Contrastive Clustering

Huasong Zhong, Jianlong Wu, Chong Chen +5

Recently, some contrastive learning methods have been proposed to simultaneously learn representations and clustering assignments, achieving significant improvements. However, thes…

cs.AI2021★ 32 cited

Efficient Non-Sampling Knowledge Graph Embedding

Zelong Li, Jianchao Ji, Zuohui Fu +4

Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negat…