Search Results for author: Wentao Zhang

Found 16 papers, 7 papers with code

K-Core Decomposition on Super Large Graphs with Limited Resources

no code implementations26 Dec 2021 Shicheng Gao, Jie Xu, Xiaosen Li, Fangcheng Fu, Wentao Zhang, Wen Ouyang, Yangyu Tao, Bin Cui

For example, the distributed K-core decomposition algorithm can scale to a large graph with 136 billion edges without losing correctness with our divide-and-conquer technique.

RIM: Reliable Influence-based Active Learning on Graphs

1 code implementation NeurIPS 2021 Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang, Jiulong Shan, Zhi Yang, Bin Cui

Message passing is the core of most graph models such as Graph Convolutional Network (GCN) and Label Propagation (LP), which usually require a large number of clean labeled data to smooth out the neighborhood over the graph.

Active Learning Graph Convolutional Network

Graph Attention Multi-Layer Perceptron

1 code implementation23 Aug 2021 Wentao Zhang, Ziqi Yin, Zeang Sheng, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui

Graph neural networks (GNNs) have recently achieved state-of-the-art performance in many graph-based applications.

Graph Attention

Coordination on Time-Varying Antagonistic Networks

no code implementations9 Aug 2021 Wentao Zhang

This paper studies coordination problem for time-varying networks suffering from antagonistic information, quantified by scaling parameters.

Evaluating Deep Graph Neural Networks

no code implementations2 Aug 2021 Wentao Zhang, Zeang Sheng, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui

Based on the experimental results, we answer the following two essential questions: (1) what actually leads to the compromised performance of deep GNNs; (2) when we need and how to build deep GNNs.

Graph Mining Node Classification

Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization

1 code implementation31 Jul 2021 Wentao Zhang, Zhi Yang, Yexin Wang, Yu Shen, Yang Li, Liang Wang, Bin Cui

Data selection methods, such as active learning and core-set selection, are useful tools for improving the data efficiency of deep learning models on large-scale datasets.

Active Learning Knowledge Graphs

ROD: Reception-aware Online Distillation for Sparse Graphs

1 code implementation25 Jul 2021 Wentao Zhang, Yuezihan Jiang, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, Bin Cui

Unfortunately, many real-world networks are sparse in terms of both edges and labels, leading to sub-optimal performance of GNNs.

Graph Learning Knowledge Distillation +4

VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition

3 code implementations19 Jul 2021 Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui

End-to-end AutoML has attracted intensive interests from both academia and industry, which automatically searches for ML pipelines in a space induced by feature engineering, algorithm/model selection, and hyper-parameter tuning.

AutoML Feature Engineering +1

OpenBox: A Generalized Black-box Optimization Service

6 code implementations1 Jun 2021 Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui

Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, engineering, physics, and experimental design.

Experimental Design Transfer Learning

GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing

no code implementations20 Apr 2021 Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui

In recent studies, neural message passing has proved to be an effective way to design graph neural networks (GNNs), which have achieved state-of-the-art performance in many graph-based tasks.

A Two-Functional-Network Framework of Opinion Dynamics

no code implementations27 Jan 2021 Wentao Zhang, Zhiqiang Zuo, Yijing Wang

A common trait involving the opinion dynamics in social networks is an anchor on interacting network to characterize the opinion formation process among participating social actors, such as information flow, cooperative and antagonistic influence, etc.

Optical manipulation of electronic dimensionality in a quantum material

no code implementations21 Jan 2021 Shaofeng Duan, Yun Cheng, Wei Xia, Yuanyuan Yang, Fengfeng Qi, Tianwei Tang, Yanfeng Guo, Dong Qian, Dao Xiang, Jie Zhang, Wentao Zhang

Exotic phenomenon can be achieved in quantum materials by confining electronic states into two dimensions.

Strongly Correlated Electrons Materials Science Superconductivity

Graph Neural Networks in Recommender Systems: A Survey

no code implementations4 Nov 2020 Shiwen Wu, Fei Sun, Wentao Zhang, Bin Cui

In this survey, we provide a comprehensive review of the most recent works on GNN-based recommender systems.

Recommendation Systems Representation Learning

DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition

no code implementations10 Oct 2019 Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang

Despite the wide application of Graph Convolutional Network (GCN), one major limitation is that it does not benefit from the increasing depth and suffers from the oversmoothing problem.

Graph Convolutional Network

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