Privacy for Free: How does Dataset Condensation Help Privacy?

1 June 2022

Papers citing "Privacy for Free: How does Dataset Condensation Help Privacy?"

35 / 35 papers shown

Title
Rethinking Federated Graph Learning: A Data Condensation Perspective Hao Zhang Miao Hu Yinlin Zhu Lianglin Hu FedML DD AI4CE 105 0 0 05 May 2025
Dataset Distillation with Neural Characteristic Function: A Minmax Perspective Shaobo Wang Yicun Yang Ziqiang Liu Chenghao Sun Xuming Hu Conghui He Li Zhang DD 157 10 0 28 Feb 2025
Does Training with Synthetic Data Truly Protect Privacy? Yunpeng Zhao Jie Zhang 150 1 0 18 Feb 2025
Trustworthy AI: Safety, Bias, and Privacy -- A Survey Xingli Fang Jianwei Li Varun Mulchandani Jung-Eun Kim 101 0 0 11 Feb 2025
Emphasizing Discriminative Features for Dataset Distillation in Complex Scenarios Kai Wang Zekai Li Zhi-Qi Cheng Samir Khaki A. Sajedi Ramakrishna Vedantam Konstantinos N. Plataniotis Alexander G. Hauptmann Yang You DD 165 6 0 22 Oct 2024
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks S. Joshi Jiayi Ni Baharan Mirzasoleiman DD 214 2 0 03 Oct 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 93 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 130 6 0 22 Aug 2024
Breaking Resource Barriers in Speech Emotion Recognition via Data Distillation Yi-Fen Chang Zhao Ren Zhonghao Zhao Thanh Tam Nguyen Kun Qian Tanja Schultz Björn W. Schuller 80 0 0 21 Jun 2024
Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors Chun-Yin Huang Kartik Srinivas Xin Zhang Xiaoxiao Li DD 138 7 0 19 May 2024
Distilled Datamodel with Reverse Gradient Matching Jingwen Ye Ruonan Yu Songhua Liu Xinchao Wang DD 118 3 0 22 Apr 2024
PairAug: What Can Augmented Image-Text Pairs Do for Radiology? Yutong Xie Qi Chen Sinuo Wang Minh-Son To Iris Lee Ee Win Khoo Kerolos Hendy Daniel Koh Yong-quan Xia Qi Wu MedIm LM&MA 100 9 0 07 Apr 2024
Disentangled Condensation for Large-scale Graphs Zhenbang Xiao Shunyu Liu Yu Wang Tongya Zheng Mingli Song Mingli Song Tongya Zheng DD 265 7 0 18 Jan 2024
Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective Ming-Yu Chung Sheng-Yen Chou Chia-Mu Yu Pin-Yu Chen Sy-Yen Kuo Tsung-Yi Ho DD 177 7 0 28 Nov 2023
PrivateLoRA For Efficient Privacy Preserving LLM Yiming Wang Yu Lin Xiaodong Zeng Guannan Zhang 109 14 0 23 Nov 2023
DataDAM: Efficient Dataset Distillation with Attention Matching A. Sajedi Samir Khaki Ehsan Amjadian Lucy Z. Liu Y. Lawryshyn Konstantinos N. Plataniotis DD 174 69 0 29 Sep 2023
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions Weiming Zhuang Chen Chen Lingjuan Lyu Chong Chen Yaochu Jin Lingjuan Lyu AIFin AI4CE 252 99 0 27 Jun 2023
DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models Shitong Shao Xiaohan Yuan Zhenming Huang Ziming Qiu Shuai Wang Kevin Zhou MedIm DiffM 71 8 0 26 Apr 2023
Loss-Curvature Matching for Dataset Selection and Condensation Seung-Jae Shin Heesun Bae DongHyeok Shin Weonyoung Joo Il-Chul Moon DD 102 27 0 08 Mar 2023
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations Hui-Po Wang Dingfan Chen Raouf Kerkouche Mario Fritz FedML DD 106 4 0 02 Feb 2023
Dataset Distillation: A Comprehensive Review Ruonan Yu Songhua Liu Xinchao Wang DD 176 132 0 17 Jan 2023
A Comprehensive Survey of Dataset Distillation Shiye Lei Dacheng Tao DD 137 94 0 13 Jan 2023
Data Distillation: A Survey Noveen Sachdeva Julian McAuley DD 124 79 0 11 Jan 2023
Accelerating Dataset Distillation via Model Augmentation Lei Zhang Jie M. Zhang Bowen Lei Subhabrata Mukherjee Xiang Pan Bo Zhao Caiwen Ding Yongbin Li Dongkuan Xu DD 149 66 0 12 Dec 2022
Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation Jiawei Du Yiding Jiang Vincent Y. F. Tan Qiufeng Wang Haizhou Li DD 106 121 0 20 Nov 2022
DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics Renjie Pi Weizhong Zhang Yueqi Xie Jiahui Gao Xiaoyu Wang Sunghun Kim Qifeng Chen DD 93 28 0 20 Nov 2022
Private Set Generation with Discriminative Information Dingfan Chen Raouf Kerkouche Mario Fritz DD 80 39 0 07 Nov 2022
Dataset Distillation via Factorization Songhua Liu Kai Wang Xingyi Yang Jingwen Ye Xinchao Wang DD 226 148 0 30 Oct 2022
No Free Lunch in "Privacy for Free: How does Dataset Condensation Help Privacy" Nicholas Carlini Vitaly Feldman Milad Nasr DD 104 18 0 29 Sep 2022
Compressed Gastric Image Generation Based on Soft-Label Dataset Distillation for Medical Data Sharing Guang Li Ren Togo Takahiro Ogawa Miki Haseyama DD 106 43 0 29 Sep 2022
Dataset Distillation Using Parameter Pruning Guang Li Ren Togo Takahiro Ogawa Miki Haseyama DD 152 22 0 29 Sep 2022
Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments Rui Song Dai Liu Da Chen Andreas Festag Carsten Trinitis Martin Schulz Alois C. Knoll DD FedML 119 66 0 24 Aug 2022
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning Yuanhao Xiong Ruochen Wang Minhao Cheng Felix X. Yu Cho-Jui Hsieh FedML DD 91 85 0 20 Jul 2022
Condensing Graphs via One-Step Gradient Matching Wei Jin Xianfeng Tang Haoming Jiang Zheng Li Danqing Zhang Jiliang Tang Bin Ying DD 109 111 0 15 Jun 2022
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 337 380 0 07 Dec 2020