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cs.CV2023
Energizing Federated Learning via Filter-Aware Attention
Ziyuan Yang, Zerui Shao, Huijie Huangfu +5
Federated learning (FL) is a promising distributed paradigm, eliminating the need for data sharing but facing challenges from data heterogeneity. Personalized parameter generation…
cs.CV2023
Autoencoders with Intrinsic Dimension Constraints for Learning Low Dimensional Image Representations
Jianzhang Zheng, Hao Shen, Jian Yang +5
Autoencoders have achieved great success in various computer vision applications. The autoencoder learns appropriate low dimensional image representations through the self-supervis…