v1v2 (latest)

AdaCliP: Adaptive Clipping for Private SGD

20 August 2019

Venkatadheeraj Pichapati

Sanjiv Kumar

Papers citing "AdaCliP: Adaptive Clipping for Private SGD"

21 / 21 papers shown

Title
Adaptive Clipping for Privacy-Preserving Few-Shot Learning: Enhancing Generalization with Limited Data Kanishka Ranaweera Dinh C. Nguyen P. Pathirana David B. Smith Ming Ding Thierry Rakotoarivelo A. Seneviratne 84 0 0 27 Mar 2025
PCDP-SGD: Improving the Convergence of Differentially Private SGD via Projection in Advance Haichao Sha Ruixuan Liu Yi-xiao Liu Hong Chen 102 1 0 06 Dec 2023
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification Bingzhe Wu Shiwan Zhao Guangyu Sun Xiaolu Zhang Zhong Su C. Zeng Zhihong Liu 60 41 0 30 May 2019
Differentially Private Model Publishing for Deep Learning Lei Yu Ling Liu C. Pu Mehmet Emre Gursoy Stacey Truex FedML 71 265 0 03 Apr 2019
Three Tools for Practical Differential Privacy K. V. D. Veen Ruben Seggers Peter Bloem Giorgio Patrini 46 39 0 07 Dec 2018
Federated Learning for Mobile Keyboard Prediction Andrew Straiton Hard Kanishka Rao Zhifeng Lin Swaroop Indra Ramaswamy Youjie Li S. Augenstein Alex Schwing M. Annavaram A. Avestimehr FedML 136 1,545 0 08 Nov 2018
Optimal Noise-Adding Mechanism in Additive Differential Privacy Quan Geng Wei Ding Ruiqi Guo Sanjiv Kumar 66 34 0 26 Sep 2018
cpSGD: Communication-efficient and differentially-private distributed SGD Naman Agarwal A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 128 491 0 27 May 2018
Differentially Private Releasing via Deep Generative Model (Technical Report) Xinyang Zhang S. Ji Ting Wang SyDa 43 71 0 05 Jan 2018
Lattice Rescoring Strategies for Long Short Term Memory Language Models in Speech Recognition Shankar Kumar M. Nirschl D. Holtmann-Rice H. Liao A. Suresh Felix X. Yu KELM 64 40 0 15 Nov 2017
Learning Differentially Private Recurrent Language Models H. B. McMahan Daniel Ramage Kunal Talwar Li Zhang FedML 70 126 0 18 Oct 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,155 0 01 Jul 2016
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 84 839 0 06 May 2016
Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 101 604 0 19 Mar 2016
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 326 18,647 0 06 Feb 2015
Grammar as a Foreign Language Oriol Vinyals Lukasz Kaiser Terry Koo Slav Petrov Ilya Sutskever Geoffrey E. Hinton 111 932 0 23 Dec 2014
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,260 0 22 Dec 2014
Differentially Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds Raef Bassily Adam D. Smith Abhradeep Thakurta FedML 138 371 0 27 May 2014
The Composition Theorem for Differential Privacy Peter Kairouz Sewoong Oh Pramod Viswanath 120 682 0 04 Nov 2013
Differentially Private Empirical Risk Minimization Kamalika Chaudhuri C. Monteleoni Anand D. Sarwate 137 1,490 0 01 Dec 2009
Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning Benjamin I. P. Rubinstein Peter L. Bartlett Ling Huang N. Taft 106 295 0 30 Nov 2009