Meta Knowledge Condensation for Federated Learning

29 September 2022

Papers citing "Meta Knowledge Condensation for Federated Learning"

22 / 22 papers shown

Title
Subgraph Federated Learning for Local Generalization Sungwon Kim Yoonho Lee Yunhak Oh Namkyeong Lee Sukwon Yun Junseok Lee Sein Kim Carl Yang Chanyoung Park FedML OOD 79 1 0 06 Mar 2025
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs Junying Chen Zhenyang Cai Ke Ji X. Wang Wanlong Liu Rongsheng Wang Jianye Hou Benyou Wang LRM 28 33 0 25 Dec 2024
Tackling Data Heterogeneity in Federated Time Series Forecasting Wei Yuan Guanhua Ye Xiangyu Zhao Quoc Viet Hung Nguyen Yang Cao Hongzhi Yin AI4TS 69 0 0 24 Nov 2024
Dataset Distillation-based Hybrid Federated Learning on Non-IID Data Xiufang Shi Wei Zhang Mincheng Wu Guangyi Liu Z. Wen Shibo He Tejal Shah R. Ranjan DD FedML 21 1 0 26 Sep 2024
Not All Samples Should Be Utilized Equally: Towards Understanding and Improving Dataset Distillation Shaobo Wang Yantai Yang Qilong Wang Kaixin Li Linfeng Zhang Junchi Yan DD 41 4 0 22 Aug 2024
One-Shot Collaborative Data Distillation William Holland Chandra Thapa Sarah Ali Siddiqui Wei Shao S. Çamtepe DD FedML 30 0 0 05 Aug 2024
Speech Emotion Recognition under Resource Constraints with Data Distillation Yi Chang Zhao Ren Zhonghao Zhao Thanh Tam Nguyen Kun Qian Tanja Schultz Björn W. Schuller 19 0 0 21 Jun 2024
ATOM: Attention Mixer for Efficient Dataset Distillation Samir Khaki A. Sajedi Kai Wang Lucy Z. Liu Y. Lawryshyn Konstantinos N. Plataniotis 38 3 0 02 May 2024
An Aggregation-Free Federated Learning for Tackling Data Heterogeneity Yuan Wang Huazhu Fu Renuga Kanagavelu Qingsong Wei Yong Liu Rick Siow Mong Goh FedML 18 28 0 29 Apr 2024
DD-RobustBench: An Adversarial Robustness Benchmark for Dataset Distillation Yifan Wu Jiawei Du Ping Liu Yuewei Lin Wenqing Cheng Wei-ping Xu DD AAML 38 5 0 20 Mar 2024
Group Distributionally Robust Dataset Distillation with Risk Minimization Saeed Vahidian Mingyu Wang Jianyang Gu Vyacheslav Kungurtsev Wei Jiang Yiran Chen OOD DD 31 6 0 07 Feb 2024
Importance-Aware Adaptive Dataset Distillation Guang Li Ren Togo Takahiro Ogawa Miki Haseyama DD 19 6 0 29 Jan 2024
Efficient Dataset Distillation via Minimax Diffusion Jianyang Gu Saeed Vahidian Vyacheslav Kungurtsev Haonan Wang Wei Jiang Yang You Yiran Chen DD 35 26 0 27 Nov 2023
Sequential Subset Matching for Dataset Distillation Jiawei Du Qin Shi Joey Tianyi Zhou DD 29 27 0 02 Nov 2023
AST: Effective Dataset Distillation through Alignment with Smooth and High-Quality Expert Trajectories Jiyuan Shen Wenzhuo Yang Kwok-Yan Lam DD 23 1 0 16 Oct 2023
Can pre-trained models assist in dataset distillation? Yao Lu Xuguang Chen Yuchen Zhang Jianyang Gu Tianle Zhang Yifan Zhang Xiaoniu Yang Qi Xuan Kai Wang Yang You DD 32 10 0 05 Oct 2023
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency Jiawei Shao Zijian Li Wenqiang Sun Tailin Zhou Yuchang Sun Lumin Liu Zehong Lin Yuyi Mao Jun Zhang FedML 26 22 0 20 Jul 2023
Dataset Distillation: A Comprehensive Review Ruonan Yu Songhua Liu Xinchao Wang DD 35 121 0 17 Jan 2023
A Comprehensive Survey of Dataset Distillation Shiye Lei Dacheng Tao DD 31 87 0 13 Jan 2023
Data Distillation: A Survey Noveen Sachdeva Julian McAuley DD 22 73 0 11 Jan 2023
Dataset Condensation with Differentiable Siamese Augmentation Bo-Lu Zhao Hakan Bilen DD 189 288 0 16 Feb 2021
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning Giulia Denevi Massimiliano Pontil C. Ciliberto 32 39 0 25 Aug 2020