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DENSE: Data-Free One-Shot Federated Learning

DENSE: Data-Free One-Shot Federated Learning

23 December 2021
Jie M. Zhang
Chen Chen
Bo-wen Li
Lingjuan Lyu
Shuang Wu
Shouhong Ding
Chunhua Shen
Chao Wu
    FedML
    DD
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Papers citing "DENSE: Data-Free One-Shot Federated Learning"

22 / 22 papers shown
Title
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
Jacopo Talpini
Marco Savi
Giovanni Neglia
FedML
Presented at ResearchTrend Connect | FedML on 07 May 2025
76
0
0
19 Mar 2025
Capture Global Feature Statistics for One-Shot Federated Learning
Zenghao Guan
Yucan Zhou
Xiaoyan Gu
FedML
63
0
0
10 Mar 2025
A Unified Solution to Diverse Heterogeneities in One-shot Federated Learning
A Unified Solution to Diverse Heterogeneities in One-shot Federated Learning
Jun Bai
Yiliao Song
Di Wu
Atul Sajjanhar
Yong Xiang
Wei Zhou
Xiaohui Tao
Yan Li
Y. Li
FedML
53
0
0
28 Oct 2024
Few-Shot Class-Incremental Learning with Non-IID Decentralized Data
Few-Shot Class-Incremental Learning with Non-IID Decentralized Data
Cuiwei Liu
Siang Xu
Huaijun Qiu
Jing Zhang
Zhi Liu
Liang Zhao
CLL
32
0
0
18 Sep 2024
A Systematic Review of Federated Generative Models
A Systematic Review of Federated Generative Models
Ashkan Vedadi Gargary
Emiliano De Cristofaro
AI4CE
36
2
0
26 May 2024
Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors
Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors
Chun-Yin Huang
Kartik Srinivas
Xin Zhang
Xiaoxiao Li
DD
48
6
0
19 May 2024
DiLM: Distilling Dataset into Language Model for Text-level Dataset
  Distillation
DiLM: Distilling Dataset into Language Model for Text-level Dataset Distillation
Aru Maekawa
Satoshi Kosugi
Kotaro Funakoshi
Manabu Okumura
DD
39
10
0
30 Mar 2024
Sampling to Distill: Knowledge Transfer from Open-World Data
Sampling to Distill: Knowledge Transfer from Open-World Data
Yuzheng Wang
Zhaoyu Chen
Jie M. Zhang
Dingkang Yang
Zuhao Ge
Yang Liu
Siao Liu
Yunquan Sun
Wenqiang Zhang
Lizhe Qi
26
9
0
31 Jul 2023
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
Weiming Zhuang
Chen Chen
Lingjuan Lyu
C. L. P. Chen
Yaochu Jin
Lingjuan Lyu
AIFin
AI4CE
99
85
0
27 Jun 2023
Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
Zixuan Hu
Li Shen
Zhenyi Wang
Baoyuan Wu
Chun Yuan
Dacheng Tao
47
7
0
28 May 2023
Generalized Universal Domain Adaptation with Generative Flow Networks
Generalized Universal Domain Adaptation with Generative Flow Networks
Didi Zhu
Yinchuan Li
Yunfeng Shao
Jianye Hao
Fei Wu
Kun Kuang
Jun Xiao
Chao Wu
AI4CE
OOD
34
16
0
08 May 2023
FedPNN: One-shot Federated Classification via Evolving Clustering Method
  and Probabilistic Neural Network hybrid
FedPNN: One-shot Federated Classification via Evolving Clustering Method and Probabilistic Neural Network hybrid
Polaki Durga Prasad
Yelleti Vivek
V. Ravi
FedML
23
0
0
09 Apr 2023
No Fear of Classifier Biases: Neural Collapse Inspired Federated
  Learning with Synthetic and Fixed Classifier
No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier
Zexi Li
Xinyi Shang
Rui He
Tao R. Lin
Chao Wu
FedML
39
54
0
17 Mar 2023
Delving into the Adversarial Robustness of Federated Learning
Delving into the Adversarial Robustness of Federated Learning
Jie M. Zhang
Bo-wen Li
Chen Chen
Lingjuan Lyu
Shuang Wu
Shouhong Ding
Chao Wu
FedML
32
34
0
19 Feb 2023
Local Model Reconstruction Attacks in Federated Learning and their Uses
Ilias Driouich
Chuan Xu
Giovanni Neglia
F. Giroire
Eoin Thomas
AAML
FedML
27
2
0
28 Oct 2022
IDEAL: Query-Efficient Data-Free Learning from Black-box Models
IDEAL: Query-Efficient Data-Free Learning from Black-box Models
Jie M. Zhang
Chen Chen
Lingjuan Lyu
55
14
0
23 May 2022
A Secure and Efficient Federated Learning Framework for NLP
A Secure and Efficient Federated Learning Framework for NLP
Jieren Deng
Chenghong Wang
Xianrui Meng
Yijue Wang
Ji Li
Sheng Lin
Shuo Han
Fei Miao
Sanguthevar Rajasekaran
Caiwen Ding
FedML
69
22
0
28 Jan 2022
CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for
  Combating Deepfakes
CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes
Hao Huang
Yongtao Wang
Zhaoyu Chen
Yuze Zhang
Yuheng Li
Zhi Tang
Wei Chu
Jingdong Chen
Weisi Lin
K. Ma
AAML
62
90
0
23 May 2021
FedBN: Federated Learning on Non-IID Features via Local Batch
  Normalization
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
Xiaoxiao Li
Meirui Jiang
Xiaofei Zhang
Michael Kamp
Qi Dou
OOD
FedML
168
787
0
15 Feb 2021
Federated Learning on Non-IID Data Silos: An Experimental Study
Federated Learning on Non-IID Data Silos: An Experimental Study
Q. Li
Yiqun Diao
Quan Chen
Bingsheng He
FedML
OOD
87
946
0
03 Feb 2021
Incremental Embedding Learning via Zero-Shot Translation
Incremental Embedding Learning via Zero-Shot Translation
Kun-Juan Wei
Cheng Deng
Xu Yang
Maosen Li
CLL
28
21
0
31 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses
Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu
Han Yu
Xingjun Ma
Chen Chen
Lichao Sun
Jun Zhao
Qiang Yang
Philip S. Yu
FedML
180
355
0
07 Dec 2020
1