Tempered Sigmoid Activations for Deep Learning with Differential Privacy

28 July 2020

Papers citing "Tempered Sigmoid Activations for Deep Learning with Differential Privacy"

29 / 29 papers shown

Title
Crowding Out The Noise: Algorithmic Collective Action Under Differential Privacy Rushabh Solanki Meghana Bhange Ulrich Aïvodji Elliot Creager 29 0 0 09 May 2025
DC-SGD: Differentially Private SGD with Dynamic Clipping through Gradient Norm Distribution Estimation Chengkun Wei Weixian Li Chen Gong Wenzhi Chen 58 0 0 29 Mar 2025
Privacy-Preserving Dataset Combination Keren Fuentes Mimee Xu Irene Chen 38 0 0 09 Feb 2025
Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions Zhihao He Hang Yu Zi Gong Shizhan Liu J. Li Weiyao Lin VLM 38 1 0 09 Oct 2024
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction Xinwei Zhang Zhiqi Bu Borja Balle Mingyi Hong Meisam Razaviyayn Vahab Mirrokni 76 2 0 04 Oct 2024
Learning Privacy-Preserving Student Networks via Discriminative-Generative Distillation Shiming Ge Bochao Liu Pengju Wang Yong Li Dan Zeng FedML 42 9 0 04 Sep 2024
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy Georgios Kaissis Stefan Kolek Borja Balle Jamie Hayes Daniel Rueckert 47 4 0 13 Jun 2024
DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning Yixuan Liu Li Xiong Yuhan Liu Yujie Gu Ruixuan Liu Hong Chen 38 1 0 04 Jun 2024
Delving into Differentially Private Transformer Youlong Ding Xueyang Wu Yining Meng Yonggang Luo Hao Wang Weike Pan 36 5 0 28 May 2024
Protecting User Privacy in Remote Conversational Systems: A Privacy-Preserving framework based on text sanitization Zhigang Kan Linbo Qiao Hao Yu Liwen Peng Yifu Gao Dongsheng Li 26 20 0 14 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
Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks Ferheen Ayaz Idris Zakariyya José Cano S. Keoh Jeremy Singer D. Pau Mounia Kharbouche-Harrari 19 5 0 25 Apr 2023
Communication and Energy Efficient Wireless Federated Learning with Intrinsic Privacy Zhenxiao Zhang Yuanxiong Guo Yuguang Fang Yanmin Gong 28 4 0 15 Apr 2023
SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing Jie Fu Zhili Chen Xinpeng Ling 22 0 0 14 Nov 2022
MuMIC -- Multimodal Embedding for Multi-label Image Classification with Tempered Sigmoid Feng Wang Sarai Mizrachi Moran Beladev Guy Nadav Gil Amsalem Karen Lastmann Assaraf Hadas Harush Boker VLM 22 13 0 02 Nov 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Y. Yang 46 20 0 18 Oct 2022
Fine-Tuning with Differential Privacy Necessitates an Additional Hyperparameter Search Yannis Cattan Christopher A. Choquette-Choo Nicolas Papernot Abhradeep Thakurta 26 20 0 05 Oct 2022
On the Evaluation of User Privacy in Deep Neural Networks using Timing Side Channel Shubhi Shukla Manaar Alam Sarani Bhattacharya Debdeep Mukhopadhyay Pabitra Mitra AAML 25 2 0 01 Aug 2022
Beyond Uniform Lipschitz Condition in Differentially Private Optimization Rudrajit Das Satyen Kale Zheng Xu Tong Zhang Sujay Sanghavi 24 17 0 21 Jun 2022
Differentially Private Speaker Anonymization Ali Shahin Shamsabadi B. M. L. Srivastava A. Bellet Nathalie Vauquier Emmanuel Vincent Mohamed Maouche Marc Tommasi Nicolas Papernot MIACV 38 32 0 23 Feb 2022
Toward Training at ImageNet Scale with Differential Privacy Alexey Kurakin Shuang Song Steve Chien Roxana Geambasu Andreas Terzis Abhradeep Thakurta 33 100 0 28 Jan 2022
Improving Differentially Private SGD via Randomly Sparsified Gradients Junyi Zhu Matthew B. Blaschko 26 5 0 01 Dec 2021
Public Data-Assisted Mirror Descent for Private Model Training Ehsan Amid Arun Ganesh Rajiv Mathews Swaroop Indra Ramaswamy Shuang Song Thomas Steinke Vinith M. Suriyakumar Om Thakkar Abhradeep Thakurta 8 49 0 01 Dec 2021
Not all noise is accounted equally: How differentially private learning benefits from large sampling rates Friedrich Dörmann Osvald Frisk L. Andersen Christian Fischer Pedersen FedML 59 25 0 12 Oct 2021
An automatic differentiation system for the age of differential privacy Dmitrii Usynin Alexander Ziller Moritz Knolle Andrew Trask Kritika Prakash Daniel Rueckert Georgios Kaissis 28 3 0 22 Sep 2021
Selective Differential Privacy for Language Modeling Weiyan Shi Aiqi Cui Evan Li R. Jia Zhou Yu 18 68 0 30 Aug 2021
Efficient Hyperparameter Optimization for Differentially Private Deep Learning Aman Priyanshu Rakshit Naidu Fatemehsadat Mireshghallah Mohammad Malekzadeh 22 5 0 09 Aug 2021
Adaptive Machine Unlearning Varun Gupta Christopher Jung Seth Neel Aaron Roth Saeed Sharifi-Malvajerdi Chris Waites MU 11 174 0 08 Jun 2021
Deep Learning with Label Differential Privacy Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Chiyuan Zhang 42 144 0 11 Feb 2021