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cs.LG2021
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…
cs.LG2020★ 2 cited
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…