1.2k citations · 2.5k across the 71 of their papers we have counts for
11 papers · 1 filter
Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem
Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas +1
Understanding the representational power of Deep Neural Networks (DNNs) and how their structural properties (e.g., depth, width, type of activation unit) affect the functions they…
Hyperbolic Graph Attention Network
Yiding Zhang, Xiao Wang, Xunqiang Jiang +2
Graph neural network (GNN) has shown superior performance in dealing with graphs, which has attracted considerable research attention recently. However, most of the existing GNN mo…
\emph{cm}SalGAN: RGB-D Salient Object Detection with Cross-View Generative Adversarial Networks
Bo Jiang, Zitai Zhou, Xiao Wang +2
Image salient object detection (SOD) is an active research topic in computer vision and multimedia area. Fusing complementary information of RGB and depth has been demonstrated to…
Independence Promoted Graph Disentangled Networks
Yanbei Liu, Xiao Wang, Shu Wu +1
We address the problem of disentangled representation learning with independent latent factors in graph convolutional networks (GCNs). The current methods usually learn node repres…
Multi-Component Graph Convolutional Collaborative Filtering
Xiao Wang, Ruijia Wang, Chuan Shi +2
The interactions of users and items in recommender system could be naturally modeled as a user-item bipartite graph. In recent years, we have witnessed an emerging research effort…
Eavesdrop the Composition Proportion of Training Labels in Federated Learning
Lixu Wang, Shichao Xu, Xiao Wang +1
Federated learning (FL) has recently emerged as a new form of collaborative machine learning, where a common model can be learned while keeping all the training data on local devic…