
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks
Graph Neural Network (GNN) research is rapidly growing thanks to the cap...
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QDGCN: QueryDriven Graph Convolutional Networks for Attributed Community Search
Recently, attributed community search, a related but different problem t...
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Recognizing Predictive Substructures with Subgraph Information Bottleneck
The emergence of Graph Convolutional Network (GCN) has greatly boosted t...
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Diversified Multiscale Graph Learning with Graph SelfCorrection
Though the multiscale graph learning techniques have enabled advanced fe...
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Learning DiverseStructured Networks for Adversarial Robustness
In adversarial training (AT), the main focus has been the objective and ...
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Towards ExpectationMaximization by SQL in RDBMS
Integrating machine learning techniques into RDBMSs is an important task...
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Chasing the Tail in Monocular 3D Human Reconstruction with Prototype Memory
Deep neural networks have achieved great progress in singleimage 3D hum...
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Hierarchical Graph Capsule Network
Graph Neural Networks (GNNs) draw their strength from explicitly modelin...
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Deep Multimodal Fusion by Channel Exchanging
Deep multimodal fusion by using multiple sources of data for classificat...
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On SelfDistilling Graph Neural Network
Recently, the teacherstudent knowledge distillation framework has demon...
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Graph Information Bottleneck for Subgraph Recognition
Given the input graph and its label/property, several key problems of gr...
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Dirichlet Graph Variational Autoencoder
Graph Neural Networks (GNNs) and Variational Autoencoders (VAEs) have be...
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PixelFace: A LargeScale, HighResolution Benchmark for 3D Face Reconstruction
3D face reconstruction is a fundamental task that can facilitate numerou...
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Tackling OverSmoothing for General Graph Convolutional Networks
Increasing the depth of Graph Convolutional Networks (GCN), which in pri...
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FrankMocap: Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration
Although the essential nuance of human motion is often conveyed as a com...
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Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?
Graph Identification (GI) has long been researched in graph learning and...
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Leveraging TSP Solver Complementarity via Deep Learning
The Travelling Salesman Problem (TSP) is a classical NPhard problem and...
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Spectral Graph Attention Network
Variants of Graph Neural Networks (GNNs) for representation learning hav...
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Graph Representation Learning via Graphical Mutual Information Maximization
The richness in the content of various information networks such as soci...
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Adversarial Attack on Community Detection by Hiding Individuals
It has been demonstrated that adversarial graphs, i.e., graphs with impe...
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Rumor Detection on Social Media with BiDirectional Graph Convolutional Networks
Social media has been developing rapidly in public due to its nature of ...
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Graph Convolutional Networks for Temporal Action Localization
Most stateoftheart action localization systems process each action pr...
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Delving Deep Into Hybrid Annotations for 3D Human Recovery in the Wild
Though much progress has been achieved in singleimage 3D human recovery...
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A Restricted Blackbox Adversarial Framework Towards Attacking Graph Embedding Models
With the great success of graph embedding model on both academic and ind...
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The General Blackbox Attack Method for Graph Neural Networks
With the great success of Graph Neural Networks (GNNs) towards represent...
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DropEdge: Towards the Very Deep Graph Convolutional Networks for Node Classification
Existing Graph Convolutional Networks (GCNs) are shallowthe number of...
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The Truly Deep Graph Convolutional Networks for Node Classification
Existing Graph Convolutional Networks (GCNs) are shallowthe number of...
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Unsupervised Adversarial Graph Alignment with Graph Embedding
Graph alignment, also known as network alignment, is a fundamental task ...
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Adversarial Representation Learning on LargeScale Bipartite Graphs
Graph representation on largescale bipartite graphs is central for a va...
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SemiSupervised Graph Classification: A Hierarchical Graph Perspective
Node classification and graph classification are two graph learning prob...
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Progressive Feature Alignment for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) transfers knowledge from a labelri...
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Adaptive Sampling Towards Fast Graph Representation Learning
Graph Convolutional Networks (GCNs) have become a crucial tool on learni...
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On the Acceleration of LBFGS with SecondOrder Information and Stochastic Batches
This paper proposes a framework of LBFGS based on the (approximate) sec...
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PoseRobust Face Recognition via Deep Residual Equivariant Mapping
Face recognition achieves exceptional success thanks to the emergence of...
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Yu Rong
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