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Communication-efficient-federated-continual-learning Communication-efficient federated continual learning for distributed learning system with Non-IID data Cite Zhang Z, Zhang Y, Guo D, et al. Communication-efficient federated continual learning for distributed learning system with Non-IID data[J]. Science...
Federated Class Continual Learning (FCCL) merges the challenges of distributed client learning with the need for seamless adaptation to new classes without forgetting old ones. The key challenge in FCCL is catastrophic forgetting, an issue that has been explored to some extent in Continual Learning ...
code github.com/MingruiLiu-M Faster federated optimization under second-order similarity 作者Ahmed Khaled 作者 Chi Jin 摘要Federated learning (FL) is a subfield of machine learning where multiple clients try to collaboratively learn a model over a network under communication constraints. We consider fi...
Australiahabibullah.habibullah@unisa.edu.auRyszard KowalczykUniversity of South AustraliaAdelaide, Australiaryszard.kowalczyk@unisa.edu.auABSTRACTFederated Class Incremental Learning (FCIL) is a new direction incontinual learning (CL) for addressing catastrophic forgetting andnon-IID data distribution simultaneo...
Foley, P. et al. OpenFL: the open federated learning library.Phys. Med. Biol.67, 214001 (2022). ArticleGoogle Scholar microsoft/msrflute(GitHub, 2023);https://github.com/microsoft/msrflute Bakas, S. et al. Identifying the best machine learning algorithms for brain tumor segmentation, progres...
Approaches for addressing distribution shifts and continual learning in federated settings. Autotuned federated algorithms for hyperparameters, model architectures etc. Federated learning and analytics as part of an AI lifecycle. Open-source frameworks and community for federated learning and analytics. ...
This is an official Tensorflow-2 implementation of Federated Continual Learning with Inter-Client Weighted Transfer - wyjeong/FedWeIT
Self-supervised Federated Learning New Tasks with New Features New Models New Algorithms Computer Vision Non-IID data and Continual Learning processes in Federated Learning: A long road ahead (Survey, Information Fusion 2022)[paper] Pure Classification ...
PyTorch implementation of: D. Shenaj, M. Toldo, A. Rigon and P. Zanuttigh, “Asynchronous Federated Continual Learning”, CVPR 2023 Workshop on Federated Learning for Computer Vision (FedVision). - LTTM/FedSpace