11 citations · 17 across the 4 of their papers we have counts for
4 papers
Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates
Laizhong Cui, Xiaoxin Su, Yipeng Zhou +1
Federated Learning (FL) is an emerging decentralized learning framework through which multiple clients can collaboratively train a learning model. However, a major obstacle that im…
Graph Convolution Networks Using Message Passing and Multi-Source Similarity Features for Predicting circRNA-Disease Association
Thosini Bamunu Mudiyanselage, Xiujuan Lei, Nipuna Senanayake +2
Graphs can be used to effectively represent complex data structures. Learning these irregular data in graphs is challenging and still suffers from shallow learning. Applying deep l…
Three-Stream Convolutional Networks for Video-based Person Re-Identification
Zeng Yu, Tianrui Li, Ning Yu +3
This paper aims to develop a new architecture that can make full use of the feature maps of convolutional networks. To this end, we study a number of methods for video-based person…
Reconstruction of Hidden Representation for Robust Feature Extraction
Zeng Yu, Tianrui Li, Ning Yu +3
This paper aims to develop a new and robust approach to feature representation. Motivated by the success of Auto-Encoders, we first theoretical summarize the general properties of…