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Opacus: User-Friendly Differential Privacy Library in PyTorch
25 September 2021
Ashkan Yousefpour
I. Shilov
Alexandre Sablayrolles
Davide Testuggine
Karthik Prasad
Mani Malek
John Nguyen
Sayan Gosh
Akash Bharadwaj
Jessica Zhao
Graham Cormode
Ilya Mironov
VLM
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Papers citing
"Opacus: User-Friendly Differential Privacy Library in PyTorch"
38 / 288 papers shown
Shuffle Gaussian Mechanism for Differential Privacy
Seng Pei Liew
Tsubasa Takahashi
FedML
193
2
0
20 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
621
98
0
14 Jun 2022
Self-Supervised Pretraining for Differentially Private Learning
Arash Asadian
Evan Weidner
Lei Jiang
PICV
216
3
0
14 Jun 2022
How unfair is private learning ?
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Amartya Sanyal
Yaxian Hu
Fanny Yang
FaML
FedML
329
26
0
08 Jun 2022
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
Da Yu
Gautam Kamath
Janardhan Kulkarni
Tie-Yan Liu
Jian Yin
Huishuai Zhang
597
25
0
06 Jun 2022
Auditing Differential Privacy in High Dimensions with the Kernel Quantum Rényi Divergence
Carles Domingo-Enrich
Youssef Mroueh
187
7
0
27 May 2022
Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss
Neural Information Processing Systems (NeurIPS), 2022
Jason M. Altschuler
Kunal Talwar
FedML
365
75
0
27 May 2022
DPSNN: A Differentially Private Spiking Neural Network with Temporal Enhanced Pooling
Jihang Wang
Dongcheng Zhao
Guobin Shen
Qian Zhang
Yingda Zeng
238
2
0
24 May 2022
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation
BigData Congress [Services Society] (BSS), 2022
Ljubomir Rokvic
Panayiotis Danassis
Sai Praneeth Karimireddy
Boi Faltings
TDI
280
3
0
23 May 2022
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy
Neural Information Processing Systems (NeurIPS), 2022
Zhiqi Bu
Jialin Mao
Shiyun Xu
486
58
0
21 May 2022
Kernel Normalized Convolutional Networks
Reza Nasirigerdeh
Reihaneh Torkzadehmahani
Daniel Rueckert
Georgios Kaissis
284
2
0
20 May 2022
SmoothNets: Optimizing CNN architecture design for differentially private deep learning
Nicolas W. Remerscheid
Alexander Ziller
Daniel Rueckert
Georgios Kaissis
142
7
0
09 May 2022
Can collaborative learning be private, robust and scalable?
Dmitrii Usynin
Helena Klause
Johannes C. Paetzold
Daniel Rueckert
Georgios Kaissis
FedML
MedIm
197
3
0
05 May 2022
Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?
Héber H. Arcolezi
Jean-François Couchot
Denis Renaud
Bechara al Bouna
X. Xiao
AI4TS
301
9
0
01 May 2022
Unlocking High-Accuracy Differentially Private Image Classification through Scale
Soham De
Leonard Berrada
Jamie Hayes
Samuel L. Smith
Borja Balle
401
267
0
28 Apr 2022
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Cuong Tran
Keyu Zhu
Ferdinando Fioretto
Pascal Van Hentenryck
186
12
0
11 Apr 2022
What You See is What You Get: Principled Deep Learning via Distributional Generalization
Neural Information Processing Systems (NeurIPS), 2022
B. Kulynych
Yao-Yuan Yang
Yaodong Yu
Jarosław Błasiok
Preetum Nakkiran
OOD
297
11
0
07 Apr 2022
ScaleSFL: A Sharding Solution for Blockchain-Based Federated Learning
International Symposium on Blockchain and Secure Critical Infrastructure (ISBSCI), 2022
Evan W. R. Madill
Ben Nguyen
C. Leung
Sara Rouhani
146
33
0
04 Apr 2022
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning
Computer Vision and Pattern Recognition (CVPR), 2022
Haoxiang Wang
Yite Wang
Tian Ding
Yue Liu
216
39
0
17 Mar 2022
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence)
Neural Information Processing Systems (NeurIPS), 2022
Jiayuan Ye
Reza Shokri
FedML
291
57
0
10 Mar 2022
Similarity-based Label Inference Attack against Training and Inference of Split Learning
IEEE Transactions on Information Forensics and Security (IEEE TIFS), 2022
Junlin Liu
Xinchen Lyu
Qimei Cui
Xiaofeng Tao
FedML
258
36
0
10 Mar 2022
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation
USENIX Security Symposium (USENIX Security), 2022
Sina Sajadmanesh
Ali Shahin Shamsabadi
A. Bellet
D. Gática-Pérez
282
96
0
02 Mar 2022
Differentially private training of residual networks with scale normalisation
Helena Klause
Alexander Ziller
Daniel Rueckert
Kerstin Hammernik
Georgios Kaissis
300
38
0
01 Mar 2022
Defending against Reconstruction Attacks with Rényi Differential Privacy
Pierre Stock
I. Shilov
Ilya Mironov
Alexandre Sablayrolles
AAML
SILM
MIACV
168
44
0
15 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
338
100
0
15 Feb 2022
Toward Training at ImageNet Scale with Differential Privacy
Alexey Kurakin
Shuang Song
Steve Chien
Roxana Geambasu
Seth Neel
Abhradeep Thakurta
322
116
0
28 Jan 2022
Differential Privacy Guarantees for Stochastic Gradient Langevin Dynamics
T. Ryffel
Francis R. Bach
D. Pointcheval
154
24
0
28 Jan 2022
Plume: Differential Privacy at Scale
Kareem Amin
Jennifer Gillenwater
Matthew Joseph
Alex Kulesza
Sergei Vassilvitskii
176
13
0
27 Jan 2022
Transformers in Medical Imaging: A Survey
Fahad Shamshad
Salman Khan
Syed Waqas Zamir
Muhammad Haris Khan
Munawar Hayat
Fahad Shahbaz Khan
Huazhu Fu
ViT
LM&MA
MedIm
327
967
0
24 Jan 2022
Synthesising Electronic Health Records: Cystic Fibrosis Patient Group
E. Muller
Xu Zheng
Jer Hayes
214
2
0
14 Jan 2022
Differential Privacy Made Easy
Muhammad Aitsam
SyDa
126
11
0
01 Jan 2022
On the Importance of Difficulty Calibration in Membership Inference Attacks
International Conference on Learning Representations (ICLR), 2021
Lauren Watson
Chuan Guo
Graham Cormode
Alex Sablayrolles
304
178
0
15 Nov 2021
DP-XGBoost: Private Machine Learning at Scale
Cheng Cheng
Wei Dai
168
10
0
25 Oct 2021
Can Stochastic Gradient Langevin Dynamics Provide Differential Privacy for Deep Learning?
Guy Heller
Ethan Fetaya
BDL
310
3
0
11 Oct 2021
NanoBatch Privacy: Enabling fast Differentially Private learning on the IPU
Edward H. Lee
M. M. Krell
Alexander Tsyplikhin
Victoria Rege
E. Colak
Kristen W. Yeom
FedML
174
0
0
24 Sep 2021
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization
Neural Information Processing Systems (NeurIPS), 2020
P. Subramani
Nicholas Vadivelu
Gautam Kamath
337
87
0
18 Oct 2020
Individual Privacy Accounting via a Renyi Filter
Neural Information Processing Systems (NeurIPS), 2020
Vitaly Feldman
Tijana Zrnic
551
107
0
25 Aug 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
ACM Transactions on Knowledge Discovery from Data (TKDD), 2020
Xinjian Luo
Xiangqi Zhu
FedML
663
30
0
27 Apr 2020
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