49 citations · 75 across the 9 of their papers we have counts for
9 papers
Graph Entropy Minimization for Semi-supervised Node Classification
Yi Luo, Guangchun Luo, Ke Qin +1
Node classifiers are required to comprehensively reduce prediction errors, training resources, and inference latency in the industry. However, most graph neural networks (GNN) conc…
Unifying Label-inputted Graph Neural Networks with Deep Equilibrium Models
Yi Luo, Guiduo Duan, Guangchun Luo +1
The success of Graph Neural Networks (GNN) in learning on non-Euclidean data arouses many subtopics, such as Label-inputted GNN (LGNN) and Implicit GNN (IGNN). LGNN, explicitly inp…
Self-supervised Consensus Representation Learning for Attributed Graph
Changshu Liu, Liangjian Wen, Zhao Kang +2
Attempting to fully exploit the rich information of topological structure and node features for attributed graph, we introduce self-supervised learning mechanism to graph represent…
Towards Clustering-friendly Representations: Subspace Clustering via Graph Filtering
Zhengrui Ma, Zhao Kang, Guangchun Luo +1
Finding a suitable data representation for a specific task has been shown to be crucial in many applications. The success of subspace clustering depends on the assumption that the…
Adversarial Privacy Preserving Graph Embedding against Inference Attack
Kaiyang Li, Guangchun Luo, Yang Ye +3
Recently, the surge in popularity of Internet of Things (IoT), mobile devices, social media, etc. has opened up a large source for graph data. Graph embedding has been proved extre…
Fine-Grained Image Captioning with Global-Local Discriminative Objective
Jie Wu, Tianshui Chen, Hefeng Wu +3
Significant progress has been made in recent years in image captioning, an active topic in the fields of vision and language. However, existing methods tend to yield overly general…
Sparse Label Smoothing Regularization for Person Re-Identification
Jean-Paul Ainam, Ke Qin, Guisong Liu +1
Person re-identification (re-id) is a cross-camera retrieval task which establishes a correspondence between images of a person from multiple cameras. Deep Learning methods have be…
On Dynamic Job Ordering and Slot Configurations for Minimizing the Makespan Of Multiple MapReduce Jobs
Wenhong Tian, Guangchun Luo, Ling Tian +1
MapReduce is a popular parallel computing paradigm for Big Data processing in clusters and data centers. It is observed that different job execution orders and MapReduce slot confi…
Prepartition: Paradigm for the Load Balance of Virtual Machine Allocation in Data Centers
Minxian Xu, Guangchun Luo, Ling Tian +4
It is significant to apply load-balancing strategy to improve the performance and reliability of resource in data centers. One of the challenging scheduling problems in Cloud data…