571 citations · 1.9k across the 53 of their papers we have counts for
5 papers · 1 filter
Memory Efficient Class-Incremental Learning for Image Classification
Hanbin Zhao, Hui Wang, Yongjian Fu +2
With the memory-resource-limited constraints, class-incremental learning (CIL) usually suffers from the "catastrophic forgetting" problem when updating the joint classification mod…
Federated Mutual Learning
Tao Shen, Jie Zhang, Xinkang Jia +6
Federated learning (FL) enables collaboratively training deep learning models on decentralized data. However, there are three types of heterogeneities in FL setting bringing about…
State Distribution-aware Sampling for Deep Q-learning
Weichao Li, Fuxian Huang, Xi Li +2
A critical and challenging problem in reinforcement learning is how to learn the state-action value function from the experience replay buffer and simultaneously keep sample effici…
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
Jun Xiao, Hao Ye, Xiangnan He +3
Factorization Machines (FMs) are a supervised learning approach that enhances the linear regression model by incorporating the second-order feature interactions. Despite effectiven…
Local and global approaches of affinity propagation clustering for large scale data
Dingyin Xia, Fei Wu, Xuqing Zhang +1
Recently a new clustering algorithm called 'affinity propagation' (AP) has been proposed, which efficiently clustered sparsely related data by passing messages between data points.…