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The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks
22 February 2018
Nicholas Carlini
Chang-rui Liu
Ulfar Erlingsson
Jernej Kos
Basel Alomair
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Papers citing
"The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks"
41 / 791 papers shown
Differentially Private Set Union
International Conference on Machine Learning (ICML), 2020
Sivakanth Gopi
P. Gulhane
Janardhan Kulkarni
J. Shen
Milad Shokouhi
Sergey Yekhanin
FedML
162
34
0
22 Feb 2020
Data Heterogeneity Differential Privacy: From Theory to Algorithm
International Conference on Conceptual Structures (ICCS), 2020
Yilin Kang
Jian Li
Yong Liu
Weiping Wang
160
1
0
20 Feb 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers
Machine-mediated learning (ML), 2020
Thomas Baumhauer
Pascal Schöttle
Matthias Zeppelzauer
MU
317
150
0
07 Feb 2020
CryptoSPN: Privacy-preserving Sum-Product Network Inference
European Conference on Artificial Intelligence (ECAI), 2020
Amos Treiber
Alejandro Molina
Christian Weinert
T. Schneider
Kristian Kersting
141
11
0
03 Feb 2020
Model Extraction Attacks against Recurrent Neural Networks
Tatsuya Takemura
Naoto Yanai
T. Fujiwara
MLAU
MIACV
AAML
164
15
0
01 Feb 2020
Analyzing Information Leakage of Updates to Natural Language Models
Conference on Computer and Communications Security (CCS), 2019
Santiago Zanella Béguelin
Lukas Wutschitz
Shruti Tople
Victor Rühle
Andrew Paverd
O. Ohrimenko
Boris Köpf
Marc Brockschmidt
ELM
MIACV
FedML
PILM
KELM
377
135
0
17 Dec 2019
Advances and Open Problems in Federated Learning
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
...
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
FedML
AI4CE
602
7,525
0
10 Dec 2019
Machine Unlearning
IEEE Symposium on Security and Privacy (IEEE S&P), 2019
Lucas Bourtoule
Varun Chandrasekaran
Christopher A. Choquette-Choo
Hengrui Jia
Adelin Travers
Baiwu Zhang
David Lie
Nicolas Papernot
MU
551
1,196
0
09 Dec 2019
Security of Deep Learning Methodologies: Challenges and Opportunities
Shahbaz Rezaei
Xin Liu
AAML
160
4
0
08 Dec 2019
Differentially Private Synthetic Mixed-Type Data Generation For Unsupervised Learning
U. Tantipongpipat
Chris Waites
Digvijay Boob
Amaresh Ankit Siva
Rachel Cummings
SyDa
308
31
0
06 Dec 2019
PAC learning with stable and private predictions
Annual Conference Computational Learning Theory (COLT), 2019
Y. Dagan
Vitaly Feldman
236
16
0
24 Nov 2019
Robust Anomaly Detection and Backdoor Attack Detection Via Differential Privacy
International Conference on Learning Representations (ICLR), 2019
Min Du
R. Jia
Basel Alomair
AAML
206
194
0
16 Nov 2019
Revocable Federated Learning: A Benchmark of Federated Forest
Yang Liu
Zhuo Ma
Ximeng Liu
Zhuzhu Wang
Siqi Ma
Ken Ren
FedML
MU
159
11
0
08 Nov 2019
Enhancing the Privacy of Federated Learning with Sketching
Zaoxing Liu
Tian Li
Virginia Smith
Vyas Sekar
FedML
104
22
0
05 Nov 2019
Fault Tolerance of Neural Networks in Adversarial Settings
Journal of Intelligent & Fuzzy Systems (JIFS), 2019
Vasisht Duddu
N. Pillai
D. V. Rao
V. Balas
SILM
AAML
186
12
0
30 Oct 2019
Efficient Privacy-Preserving Stochastic Nonconvex Optimization
Conference on Uncertainty in Artificial Intelligence (UAI), 2019
Lingxiao Wang
Bargav Jayaraman
David Evans
Quanquan Gu
275
33
0
30 Oct 2019
Privacy Enhanced Multimodal Neural Representations for Emotion Recognition
AAAI Conference on Artificial Intelligence (AAAI), 2019
Mimansa Jaiswal
E. Provost
230
87
0
29 Oct 2019
Thieves on Sesame Street! Model Extraction of BERT-based APIs
International Conference on Learning Representations (ICLR), 2019
Kalpesh Krishna
Gaurav Singh Tomar
Ankur P. Parikh
Nicolas Papernot
Mohit Iyyer
MIACV
MLAU
562
231
0
27 Oct 2019
Weighted Distributed Differential Privacy ERM: Convex and Non-convex
Computers & security (Comput. Secur.), 2019
Yilin Kang
Yong Liu
Weiping Wang
202
10
0
23 Oct 2019
Actor Critic with Differentially Private Critic
Jonathan Lebensold
William L. Hamilton
Borja Balle
Doina Precup
OffRL
133
10
0
14 Oct 2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019
Felix Sattler
K. Müller
Wojciech Samek
FedML
461
1,253
0
04 Oct 2019
Alleviating Privacy Attacks via Causal Learning
International Conference on Machine Learning (ICML), 2019
Shruti Tople
Amit Sharma
A. Nori
MIACV
OOD
219
32
0
27 Sep 2019
Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform
ACM SIGOPS Operating Systems Review (OSR), 2019
Mathias Lécuyer
Riley Spahn
Kiran Vodrahalli
Roxana Geambasu
Daniel J. Hsu
156
49
0
04 Sep 2019
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
Conference on Innovative Data Systems Research (CIDR), 2019
Ashvin Agrawal
Rony Chatterjee
Carlo Curino
Avrilia Floratou
Neha Godwal
...
Karla Saur
Rathijit Sen
Markus Weimer
Travis Wright
Yiwen Zhu
244
43
0
30 Aug 2019
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference
International Conference on Machine Learning (ICML), 2019
Alexandre Sablayrolles
Matthijs Douze
Yann Ollivier
Cordelia Schmid
Edouard Grave
MIACV
194
420
0
29 Aug 2019
Federated Learning: Challenges, Methods, and Future Directions
IEEE Signal Processing Magazine (IEEE SPM), 2019
Tian Li
Anit Kumar Sahu
Ameet Talwalkar
Virginia Smith
FedML
1.5K
5,410
0
21 Aug 2019
Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges
IEEE Communications Magazine (IEEE Commun. Mag.), 2019
Solmaz Niknam
Harpreet S. Dhillon
J. H. Reed
427
676
0
30 Jul 2019
The Cost of a Reductions Approach to Private Fair Optimization
Daniel Alabi
296
3
0
23 Jun 2019
Membership Privacy for Machine Learning Models Through Knowledge Transfer
Virat Shejwalkar
Amir Houmansadr
168
12
0
15 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long Tail
Symposium on the Theory of Computing (STOC), 2019
Vitaly Feldman
TDI
550
581
0
12 Jun 2019
ARCHANGEL: Tamper-proofing Video Archives using Temporal Content Hashes on the Blockchain
Tu Bui
Daniel Cooper
John Collomosse
Mark Bell
Alex Green
...
Jez Higgins
Arindra Das
Jared Keller
Olivier Thereaux
Alan W. Brown
62
22
0
26 Apr 2019
How You Act Tells a Lot: Privacy-Leakage Attack on Deep Reinforcement Learning
Xinlei Pan
Weiyao Wang
Xiaoshuai Zhang
Yue Liu
Jinfeng Yi
Basel Alomair
MIACV
205
26
0
24 Apr 2019
Federated Learning Of Out-Of-Vocabulary Words
Mingqing Chen
Rajiv Mathews
Tom Y. Ouyang
F. Beaufays
FedML
219
177
0
26 Mar 2019
Déjà Vu: an empirical evaluation of the memorization properties of ConvNets
Alexandre Sablayrolles
Matthijs Douze
Cordelia Schmid
Edouard Grave
131
18
0
17 Sep 2018
Machine Learning with Membership Privacy using Adversarial Regularization
Conference on Computer and Communications Security (CCS), 2018
Milad Nasr
Reza Shokri
Amir Houmansadr
FedML
MIACV
251
520
0
16 Jul 2018
Model Reconstruction from Model Explanations
S. Milli
Ludwig Schmidt
Anca Dragan
Moritz Hardt
FAtt
169
190
0
13 Jul 2018
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Neural Information Processing Systems (NeurIPS), 2018
Joshua Allen
Bolin Ding
Janardhan Kulkarni
Harsha Nori
O. Ohrimenko
Sergey Yekhanin
SyDa
FedML
258
33
0
02 Jul 2018
How To Backdoor Federated Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2018
Eugene Bagdasaryan
Andreas Veit
Yiqing Hua
D. Estrin
Vitaly Shmatikov
SILM
FedML
541
2,281
0
02 Jul 2018
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm
Christopher DeCarolis
Mukul Ram
Seyed-Alireza Esmaeili
Yu-Xiang Wang
Furong Huang
FedML
262
12
0
25 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning
Luca Melis
Congzheng Song
Emiliano De Cristofaro
Vitaly Shmatikov
FedML
514
1,651
0
10 May 2018
Adversarial Training Versus Weight Decay
A. Galloway
T. Tanay
Graham W. Taylor
AAML
225
23
0
10 Apr 2018
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