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1905.03871
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Differentially Private Learning with Adaptive Clipping
Neural Information Processing Systems (NeurIPS), 2019
9 May 2019
Galen Andrew
Om Thakkar
H. B. McMahan
Swaroop Ramaswamy
FedML
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Papers citing
"Differentially Private Learning with Adaptive Clipping"
50 / 201 papers shown
Federated Automatic Differentiation
Keith Rush
Zachary B. Charles
Zachary Garrett
FedML
279
1
0
18 Jan 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
International Conference on Learning Representations (ICLR), 2022
Jiyan He
Xuechen Li
Da Yu
Huishuai Zhang
Janardhan Kulkarni
Y. Lee
A. Backurs
Nenghai Yu
Jiang Bian
348
58
0
03 Dec 2022
Differentially Private Learning with Per-Sample Adaptive Clipping
AAAI Conference on Artificial Intelligence (AAAI), 2022
Tianyu Xia
Shuheng Shen
Su Yao
Xinyi Fu
Ke Xu
Xiaolong Xu
Xingbo Fu
499
27
0
01 Dec 2022
Adap DP-FL: Differentially Private Federated Learning with Adaptive Noise
International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2022
Jie Fu
Zhili Chen
Xiao Han
FedML
204
42
0
29 Nov 2022
Differentially Private Image Classification from Features
Harsh Mehta
Walid Krichene
Abhradeep Thakurta
Alexey Kurakin
Ashok Cutkosky
239
10
0
24 Nov 2022
Private Ad Modeling with DP-SGD
Carson E. Denison
Badih Ghazi
Pritish Kamath
Ravi Kumar
Pasin Manurangsi
Krishnagiri Narra
Amer Sinha
A. Varadarajan
Chiyuan Zhang
367
15
0
21 Nov 2022
Learning to Generate Image Embeddings with User-level Differential Privacy
Computer Vision and Pattern Recognition (CVPR), 2022
Zheng Xu
Maxwell D. Collins
Yuxiao Wang
Liviu Panait
Sewoong Oh
S. Augenstein
Ting Liu
Florian Schroff
H. B. McMahan
FedML
283
35
0
20 Nov 2022
Differentially Private Vertical Federated Learning
Thilina Ranbaduge
Ming Ding
FedML
156
16
0
13 Nov 2022
Privacy-preserving Non-negative Matrix Factorization with Outliers
ACM Transactions on Knowledge Discovery from Data (TKDD), 2022
Swapnil Saha
H. Imtiaz
PICV
246
6
0
02 Nov 2022
On the Interaction Between Differential Privacy and Gradient Compression in Deep Learning
Jimmy J. Lin
149
0
0
01 Nov 2022
DPVIm: Differentially Private Variational Inference Improved
Hibiki Ito
Lukas Prediger
Antti Honkela
Samuel Kaski
197
3
0
28 Oct 2022
Learning-Augmented Private Algorithms for Multiple Quantile Release
International Conference on Machine Learning (ICML), 2022
M. Khodak
Kareem Amin
Travis Dick
Sergei Vassilvitskii
FedML
268
5
0
20 Oct 2022
Differentially Private Deep Learning with ModelMix
Hanshen Xiao
Jun Wan
S. Devadas
246
5
0
07 Oct 2022
Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints
Proceedings on Privacy Enhancing Technologies (PoPETs), 2022
Virat Shejwalkar
Arun Ganesh
Rajiv Mathews
Om Thakkar
Abhradeep Thakurta
182
8
0
04 Oct 2022
Taming Fat-Tailed ("Heavier-Tailed'' with Potentially Infinite Variance) Noise in Federated Learning
Neural Information Processing Systems (NeurIPS), 2022
Haibo Yang
Pei-Yuan Qiu
Jia Liu
FedML
343
17
0
03 Oct 2022
Sparse Random Networks for Communication-Efficient Federated Learning
International Conference on Learning Representations (ICLR), 2022
Berivan Isik
Francesco Pase
Deniz Gunduz
Tsachy Weissman
M. Zorzi
FedML
212
63
0
30 Sep 2022
Privacy-Preserving Online Content Moderation: A Federated Learning Use Case
The Web Conference (WWW), 2022
Pantelitsa Leonidou
N. Kourtellis
Nikos Salamanos
Michael Sirivianos
116
3
0
23 Sep 2022
Private Stochastic Optimization With Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses
Journal of Privacy and Confidentiality (JPC), 2022
Andrew Lowy
Meisam Razaviyayn
346
1
0
15 Sep 2022
Privacy-Preserving Deep Learning Model for Covid-19 Disease Detection
Hawaii International Conference on System Sciences (HICSS), 2022
Vijay Srinivas Tida
Sonya Hsu
X. Hei
MedIm
310
6
0
07 Sep 2022
FLAIR: Federated Learning Annotated Image Repository
Neural Information Processing Systems (NeurIPS), 2022
Congzheng Song
Filip Granqvist
Kunal Talwar
FedML
202
33
0
18 Jul 2022
(Nearly) Optimal Private Linear Regression via Adaptive Clipping
Prateeksha Varshney
Abhradeep Thakurta
Prateek Jain
184
9
0
11 Jul 2022
Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization
Xiaodong Yang
Huishuai Zhang
Wei Chen
Tie-Yan Liu
209
41
0
27 Jun 2022
Beyond Uniform Lipschitz Condition in Differentially Private Optimization
International Conference on Machine Learning (ICML), 2022
Rudrajit Das
Satyen Kale
Zheng Xu
Tong Zhang
Sujay Sanghavi
233
22
0
21 Jun 2022
On Privacy and Personalization in Cross-Silo Federated Learning
Neural Information Processing Systems (NeurIPS), 2022
Ziyu Liu
Shengyuan Hu
Zhiwei Steven Wu
Virginia Smith
FedML
299
69
0
16 Jun 2022
Disparate Impact in Differential Privacy from Gradient Misalignment
International Conference on Learning Representations (ICLR), 2022
Maria S. Esipova
Atiyeh Ashari Ghomi
Yaqiao Luo
Jesse C. Cresswell
283
41
0
15 Jun 2022
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger
Neural Information Processing Systems (NeurIPS), 2022
Zhiqi Bu
Yu Wang
Sheng Zha
George Karypis
591
96
0
14 Jun 2022
Blades: A Unified Benchmark Suite for Byzantine Attacks and Defenses in Federated Learning
International Conference on Internet-of-Things Design and Implementation (IoTDI), 2022
Shenghui Li
Edith C.H. Ngai
Fanghua Ye
Li Ju
Tianru Zhang
Thiemo Voigt
AAML
FedML
337
16
0
10 Jun 2022
Dap-FL: Federated Learning flourishes by adaptive tuning and secure aggregation
IEEE Transactions on Parallel and Distributed Systems (TPDS), 2022
Xinyuan Wei
Zilong Wang
Jiawei Chen
Haonan Yan
Xiaodong Lin
FedML
137
20
0
08 Jun 2022
Group privacy for personalized federated learning
International Conference on Information Systems Security and Privacy (ICISSP), 2022
Filippo Galli
Sayan Biswas
Kangsoo Jung
Tommaso Cucinotta
C. Palamidessi
FedML
215
17
0
07 Jun 2022
Algorithms for bounding contribution for histogram estimation under user-level privacy
International Conference on Machine Learning (ICML), 2022
Yuhan Liu
A. Suresh
Wennan Zhu
Peter Kairouz
Marco Gruteser
169
11
0
07 Jun 2022
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
Da Yu
Gautam Kamath
Janardhan Kulkarni
Tie-Yan Liu
Jian Yin
Huishuai Zhang
558
24
0
06 Jun 2022
Differentially Private Covariance Revisited
Neural Information Processing Systems (NeurIPS), 2022
Wei Dong
Yuting Liang
K. Yi
FedML
314
19
0
28 May 2022
DP-PCA: Statistically Optimal and Differentially Private PCA
Neural Information Processing Systems (NeurIPS), 2022
Xiyang Liu
Weihao Kong
Prateek Jain
Sewoong Oh
342
30
0
27 May 2022
Large Scale Transfer Learning for Differentially Private Image Classification
Harsh Mehta
Abhradeep Thakurta
Alexey Kurakin
Ashok Cutkosky
230
48
0
06 May 2022
Unlocking High-Accuracy Differentially Private Image Classification through Scale
Soham De
Leonard Berrada
Jamie Hayes
Samuel L. Smith
Borja Balle
374
264
0
28 Apr 2022
Secure Distributed/Federated Learning: Prediction-Privacy Trade-Off for Multi-Agent System
International Symposium on Information Theory (ISIT), 2022
Mohamed Ridha Znaidi
Gaurav Gupta
P. Bogdan
FedML
123
2
0
24 Apr 2022
A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations
Irene Balelli
Santiago Silva
Marco Lorenzi
FedML
268
5
0
15 Apr 2022
Privacy-Preserving Aggregation in Federated Learning: A Survey
IEEE Transactions on Big Data (TBD), 2022
Ziyao Liu
Jiale Guo
Wenzhuo Yang
Jiani Fan
Kwok-Yan Lam
Jun Zhao
FedML
275
127
0
31 Mar 2022
Towards Differential Relational Privacy and its use in Question Answering
Simone Bombari
Alessandro Achille
Zijian Wang
Yu Wang
Yusheng Xie
Kunwar Yashraj Singh
Srikar Appalaraju
Vijay Mahadevan
Stefano Soatto
171
1
0
30 Mar 2022
Statistic Selection and MCMC for Differentially Private Bayesian Estimation
Statistics and computing (Stat. Comput.), 2022
Barış Alparslan
S. Yıldırım
256
3
0
24 Mar 2022
Mixed Differential Privacy in Computer Vision
Computer Vision and Pattern Recognition (CVPR), 2022
Aditya Golatkar
Alessandro Achille
Yu Wang
Aaron Roth
Michael Kearns
Stefano Soatto
PICV
VLM
270
55
0
22 Mar 2022
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence)
Neural Information Processing Systems (NeurIPS), 2022
Jiayuan Ye
Reza Shokri
FedML
282
57
0
10 Mar 2022
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning
International Conference on Machine Learning (ICML), 2022
Wei-Ning Chen
Christopher A. Choquette-Choo
Peter Kairouz
A. Suresh
FedML
258
74
0
07 Mar 2022
Differentially Private Federated Learning with Local Regularization and Sparsification
Computer Vision and Pattern Recognition (CVPR), 2022
Anda Cheng
Peisong Wang
Xi Sheryl Zhang
Jian Cheng
FedML
228
94
0
07 Mar 2022
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams
Neural Information Processing Systems (NeurIPS), 2022
S. Denisov
H. B. McMahan
J. Rush
Adam D. Smith
Abhradeep Thakurta
FedML
443
79
0
16 Feb 2022
Federated Learning with Sparsified Model Perturbation: Improving Accuracy under Client-Level Differential Privacy
IEEE Transactions on Mobile Computing (IEEE TMC), 2022
Rui Hu
Yanmin Gong
Yuanxiong Guo
FedML
322
100
0
15 Feb 2022
OLIVE: Oblivious Federated Learning on Trusted Execution Environment against the risk of sparsification
Proceedings of the VLDB Endowment (PVLDB), 2022
Fumiyuki Kato
Yang Cao
Masatoshi Yoshikawa
FedML
216
7
0
15 Feb 2022
Private Adaptive Optimization with Side Information
International Conference on Machine Learning (ICML), 2022
Tian Li
Manzil Zaheer
Sashank J. Reddi
Virginia Smith
178
43
0
12 Feb 2022
Toward Training at ImageNet Scale with Differential Privacy
Alexey Kurakin
Shuang Song
Steve Chien
Roxana Geambasu
Seth Neel
Abhradeep Thakurta
308
111
0
28 Jan 2022
DP-FP: Differentially Private Forward Propagation for Large Models
Jian Du
Haitao Mi
139
7
0
29 Dec 2021
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