Federated Reconnaissance: Efficient, Distributed, Class-Incremental Learning

1 September 2021

Papers citing "Federated Reconnaissance: Efficient, Distributed, Class-Incremental Learning"

7 / 7 papers shown

Title
Accurate Forgetting for Heterogeneous Federated Continual Learning Abudukelimu Wuerkaixi Sen Cui J.N. Zhang Kunda Yan Bo Han Gang Niu Lei Fang Changshui Zhang Masashi Sugiyama 119 8 0 20 Feb 2025
Few-Shot Class-Incremental Learning with Non-IID Decentralized Data Cuiwei Liu Siang Xu Huaijun Qiu Jing Zhang Zhi Liu Liang Zhao CLL 34 0 0 18 Sep 2024
Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning Jinglin Liang Jin Zhong Hanlin Gu Zhongqi Lu Xingxing Tang Gang Dai Shuangping Huang Lixin Fan Qiang Yang DiffM 47 7 0 02 Sep 2024
Asynchronous Federated Continual Learning Donald Shenaj Marco Toldo Alberto Rigon Pietro Zanuttigh FedML CLL 26 34 0 07 Apr 2023
Better Generative Replay for Continual Federated Learning Daiqing Qi Handong Zhao Sheng Li FedML 27 47 0 25 Feb 2023
Ex-Model: Continual Learning from a Stream of Trained Models Antonio Carta Andrea Cossu Vincenzo Lomonaco D. Bacciu CLL 19 11 0 13 Dec 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 383 11,700 0 09 Mar 2017