FedSynth: Gradient Compression via Synthetic Data in Federated Learning

4 April 2022

Papers citing "FedSynth: Gradient Compression via Synthetic Data in Federated Learning"

26 / 26 papers shown

Title
WarmFed: Federated Learning with Warm-Start for Globalization and Personalization Via Personalized Diffusion Models Tao Feng Jie Zhang Xiangjian Li Rong Huang Huashan Liu Zhijie Wang FedML 57 0 0 05 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 30 0 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 72 0 0 24 Nov 2024
Using Synthetic Data to Mitigate Unfairness and Preserve Privacy in Collaborative Machine Learning Chia-Yuan Wu Frank E. Curtis Daniel P. Robinson DD 33 0 0 14 Sep 2024
UDD: Dataset Distillation via Mining Underutilized Regions Shiguang Wang Zhongyu Zhang Jian Cheng DD 28 0 0 29 Aug 2024
One-Shot Collaborative Data Distillation William Holland Chandra Thapa Sarah Ali Siddiqui Wei Shao S. Çamtepe DD FedML 32 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 24 0 0 21 Jun 2024
Federated Learning Optimization: A Comparative Study of Data and Model Exchange Strategies in Dynamic Networks Alka Luqman Yeow Wei Liang Brandon Anupam Chattopadhyay 18 0 0 16 Jun 2024
One-Shot Federated Learning with Bayesian Pseudocoresets Tim d'Hondt Mykola Pechenizkiy Robert Peharz FedML 34 0 0 04 Jun 2024
Stable Diffusion-based Data Augmentation for Federated Learning with Non-IID Data Mahdi Morafah M. Reisser Bill Lin Christos Louizos FedML 32 5 0 13 May 2024
Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents Yuqi Jia Saeed Vahidian Jingwei Sun Jianyi Zhang Vyacheslav Kungurtsev Neil Zhenqiang Gong Yiran Chen FedML DD 15 6 0 03 Dec 2023
Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching Shitong Shao Zeyuan Yin Muxin Zhou Xindong Zhang Zhiqiang Shen DD 27 21 0 29 Nov 2023
Embarassingly Simple Dataset Distillation Yunzhen Feng Ramakrishna Vedantam Julia Kempe DD 36 5 0 13 Nov 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 32 23 0 20 Jul 2023
A Client-server Deep Federated Learning for Cross-domain Surgical Image Segmentation Ronast Subedi Rebati Gaire Sharib Ali Anh Totti Nguyen Danail Stoyanov Binod Bhattarai OOD 13 2 0 14 Jun 2023
Towards Efficient Deep Hashing Retrieval: Condensing Your Data via Feature-Embedding Matching Tao Feng Jie Zhang Peizheng Wang Zhijie Wang Shengyuan Pang DD 46 0 0 29 May 2023
A Survey on Dataset Distillation: Approaches, Applications and Future Directions Jiahui Geng Zongxiong Chen Yuandou Wang Herbert Woisetschlaeger Sonja Schimmler Ruben Mayer Zhiming Zhao Chunming Rong DD 57 26 0 03 May 2023
Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation Yilin Yang Kamil Adamczewski Danica J. Sutherland Xiaoxiao Li Mijung Park 33 14 0 03 Mar 2023
Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence Yuhao Zhou Mingjia Shi Yuanxi Li Qing Ye Yanan Sun Jiancheng Lv 16 3 0 27 Feb 2023
Dataset Distillation: A Comprehensive Review Ruonan Yu Songhua Liu Xinchao Wang DD 39 121 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 37 73 0 11 Jan 2023
Backdoor Attacks Against Dataset Distillation Yugeng Liu Zheng Li Michael Backes Yun Shen Yang Zhang DD 31 27 0 03 Jan 2023
Accelerating Dataset Distillation via Model Augmentation Lei Zhang Jie M. Zhang Bowen Lei Subhabrata Mukherjee Xiang Pan Bo-Lu Zhao Caiwen Ding Y. Li Dongkuan Xu DD 32 62 0 12 Dec 2022
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 162 760 0 28 Sep 2019