Title
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning Harsh Chaudhari Giorgio Severi Alina Oprea Jonathan R. Ullman 31 5 0 05 Oct 2023
Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study Myeongseob Ko Ming Jin Chenguang Wang Ruoxi Jia 33 27 0 29 Sep 2023
Federated Learning with Differential Privacy for End-to-End Speech Recognition Martin Pelikan Sheikh Shams Azam Vitaly Feldman Jan Honza Silovsky Kunal Talwar Tatiana Likhomanenko 42 8 0 29 Sep 2023
Evaluating the Usability of Differential Privacy Tools with Data Practitioners Ivoline C. Ngong Brad Stenger Joseph P. Near Yuanyuan Feng 23 12 0 24 Sep 2023
Communication Efficient Private Federated Learning Using Dithering Burak Hasircioglu Deniz Gunduz FedML 45 7 0 14 Sep 2023
DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass Minxin Du Xiang Yue Sherman S. M. Chow Tianhao Wang Chenyu Huang Huan Sun SILM 32 58 0 13 Sep 2023
Privacy-Engineered Value Decomposition Networks for Cooperative Multi-Agent Reinforcement Learning Parham Gohari Matthew T. Hale Ufuk Topcu OffRL 30 1 0 13 Sep 2023
SABLE: Secure And Byzantine robust LEarning Antoine Choffrut R. Guerraoui Rafael Pinot Renaud Sirdey John Stephan Martin Zuber AAML 31 2 0 11 Sep 2023
Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks Daniel Scheliga Patrick Mäder M. Seeland FedML AAML 23 5 0 08 Sep 2023
Byzantine-Robust Federated Learning with Variance Reduction and Differential Privacy Zikai Zhang Rui Hu 38 11 0 07 Sep 2023
The Relative Gaussian Mechanism and its Application to Private Gradient Descent Hadrien Hendrikx Paul Mangold A. Bellet 33 1 0 29 Aug 2023
ULDP-FL: Federated Learning with Across Silo User-Level Differential Privacy Fumiyuki Kato Li Xiong Shun Takagi Yang Cao Masatoshi Yoshikawa FedML 17 3 0 23 Aug 2023
A novel analysis of utility in privacy pipelines, using Kronecker products and quantitative information flow Mário S. Alvim Natasha Fernandes Annabelle McIver Carroll Morgan Gabriel H. Nunes 19 5 0 22 Aug 2023
Differential Privacy, Linguistic Fairness, and Training Data Influence: Impossibility and Possibility Theorems for Multilingual Language Models Phillip Rust Anders Søgaard 27 3 0 17 Aug 2023
Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks Shijie Liu Andrew C. Cullen Paul Montague S. Erfani Benjamin I. P. Rubinstein AAML 23 3 0 15 Aug 2023
Large-Scale Public Data Improves Differentially Private Image Generation Quality Ruihan Wu Chuan Guo Kamalika Chaudhuri 21 2 0 04 Aug 2023
Deep Generative Models, Synthetic Tabular Data, and Differential Privacy: An Overview and Synthesis Conor Hassan Roberto Salomone Kerrie Mengersen 23 6 0 28 Jul 2023
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 38 13 0 27 Jul 2023
Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering Ce Feng Nuo Xu Wujie Wen Parv Venkitasubramaniam Caiwen Ding 12 4 0 25 Jul 2023
Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging Meirui Jiang Yuan Zhong Anjie Le Xiaoxiao Li Qianming Dou FedML 44 5 0 24 Jul 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 43 23 0 20 Jul 2023
Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection Eli Chien Wei-Ning Chen Chao Pan Pan Li Ayfer Özgür O. Milenkovic 36 12 0 12 Jul 2023
Differentially Private Video Activity Recognition Zelun Luo Yuliang Zou Yijin Yang Zane Durante De-An Huang Zhiding Yu Chaowei Xiao L. Fei-Fei Anima Anandkumar PICV 35 3 0 27 Jun 2023
Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity Bo-wen Li Yasin Esfandiari Mikkel N. Schmidt T. S. Alstrøm Sebastian U. Stich FedML 27 3 0 23 Jun 2023
ViP: A Differentially Private Foundation Model for Computer Vision Yaodong Yu Maziar Sanjabi Y. Ma Kamalika Chaudhuri Chuan Guo 16 12 0 15 Jun 2023
Augment then Smooth: Reconciling Differential Privacy with Certified Robustness Jiapeng Wu Atiyeh Ashari Ghomi David Glukhov Jesse C. Cresswell Franziska Boenisch Nicolas Papernot AAML 37 1 0 14 Jun 2023
Gaussian Membership Inference Privacy Tobias Leemann Martin Pawelczyk Gjergji Kasneci 22 15 0 12 Jun 2023
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy Soroosh Tayebi Arasteh Mahshad Lotfinia T. Nolte Marwin Saehn P. Isfort Christiane Kuhl S. Nebelung Georgios Kaissis Daniel Truhn MedIm 20 8 0 10 Jun 2023
Differentially Private Sharpness-Aware Training Jinseong Park Hoki Kim Yujin Choi Jaewook Lee 27 8 0 09 Jun 2023
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting Ana-Maria Cretu Daniel Jones Yves-Alexandre de Montjoye Shruti Tople AAML 24 4 0 08 Jun 2023
Differentially Private Image Classification by Learning Priors from Random Processes Xinyu Tang Ashwinee Panda Vikash Sehwag Prateek Mittal 23 20 0 08 Jun 2023
Privately generating tabular data using language models Alexandre Sablayrolles Yue Wang Brian Karrer LMTD 16 4 0 07 Jun 2023
Sample-Level Weighting for Multi-Task Learning with Auxiliary Tasks Emilie Grégoire M. H. Chaudhary Sam Verboven 24 1 0 07 Jun 2023
PILLAR: How to make semi-private learning more effective Francesco Pinto Yaxian Hu Fanny Yang Amartya Sanyal 46 11 0 06 Jun 2023
Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning Umang Gupta Aram Galstyan Greg Ver Steeg 6 2 0 30 May 2023
Training Private Models That Know What They Don't Know Stephan Rabanser Anvith Thudi Abhradeep Thakurta Krishnamurthy Dvijotham Nicolas Papernot 24 7 0 28 May 2023
DPFormer: Learning Differentially Private Transformer on Long-Tailed Data Youlong Ding Xueyang Wu Hongya Wang Weike Pan 31 0 0 28 May 2023
DP-SGD Without Clipping: The Lipschitz Neural Network Way Louis Bethune Thomas Massena Thibaut Boissin Yannick Prudent Corentin Friedrich Franck Mamalet A. Bellet M. Serrurier David Vigouroux 34 9 0 25 May 2023
Differentially Private Latent Diffusion Models Saiyue Lyu Michael F. Liu Margarita Vinaroz Mijung Park 26 24 0 25 May 2023
Personalized DP-SGD using Sampling Mechanisms Geon Heo Junseok Seo Steven Euijong Whang 22 2 0 24 May 2023
Trade-Offs Between Fairness and Privacy in Language Modeling Cleo Matzken Steffen Eger Ivan Habernal SILM 41 6 0 24 May 2023
Differentially Private Synthetic Data via Foundation Model APIs 1: Images Zinan Lin Sivakanth Gopi Janardhan Kulkarni Harsha Nori Sergey Yekhanin 41 36 0 24 May 2023
Privacy Loss of Noisy Stochastic Gradient Descent Might Converge Even for Non-Convex Losses S. Asoodeh Mario Díaz 20 6 0 17 May 2023
Privacy-Preserving Taxi-Demand Prediction Using Federated Learning Yumeki Goto Tomoya Matsumoto Hamada Rizk Naoto Yanai Hirozumi Yamaguchi 30 6 0 14 May 2023
MetaMorphosis: Task-oriented Privacy Cognizant Feature Generation for Multi-task Learning Md. Adnan Arefeen Zhouyu Li M. Y. S. Uddin Anupam Das 27 0 0 13 May 2023
DPMLBench: Holistic Evaluation of Differentially Private Machine Learning Chengkun Wei Ming-Hui Zhao Zhikun Zhang Min Chen Wenlong Meng Bodong Liu Yuan-shuo Fan Wenzhi Chen 34 11 0 10 May 2023
Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training Dmitrii Usynin Daniel Rueckert Georgios Kaissis FedML 28 2 0 04 May 2023
Efficient Federated Learning with Enhanced Privacy via Lottery Ticket Pruning in Edge Computing Yi Shi Kang Wei Li Shen Jun Li Xueqian Wang Bo Yuan Song Guo 41 5 0 02 May 2023
Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy Yi Shi Kang Wei Li Shen Yingqi Liu Xueqian Wang Bo Yuan Dacheng Tao FedML 35 2 0 01 May 2023
The Disharmony between BN and ReLU Causes Gradient Explosion, but is Offset by the Correlation between Activations Inyoung Paik Jaesik Choi 18 0 0 23 Apr 2023