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0911.5708
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Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning
30 November 2009
Benjamin I. P. Rubinstein
Peter L. Bartlett
Ling Huang
N. Taft
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Papers citing
"Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning"
50 / 99 papers shown
Multi-Class Support Vector Machine with Differential Privacy
Jinseong Park
Yujin Choi
Jaewook Lee
156
0
0
05 Oct 2025
Purifying Approximate Differential Privacy with Randomized Post-processing
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2025
Yingyu Lin
Erchi Wang
Yi-An Ma
Yu-Xiang Wang
346
2
0
27 Mar 2025
Privacy-Preserving Brain-Computer Interfaces: A Systematic Review
IEEE Transactions on Computational Social Systems (IEEE TCSS), 2023
K. Xia
W. Duch
Y. Sun
K. Xu
W. Fang
...
Y. Zhang
D. Sang
X. Xu
F-Y Wang
D. Wu
374
49
0
16 Dec 2024
A Hybrid Federated Kernel Regularized Least Squares Algorithm
Celeste Damiani
Yulia Rodina
Sergio Decherchi
FedML
129
5
0
24 Jul 2024
SoK: A Review of Differentially Private Linear Models For High-Dimensional Data
Amol Khanna
Edward Raff
Nathan Inkawhich
257
5
0
01 Apr 2024
LLM-based Privacy Data Augmentation Guided by Knowledge Distillation with a Distribution Tutor for Medical Text Classification
Yiping Song
Juhua Zhang
Zhiliang Tian
Yuxin Yang
Shiyu Huang
Dongsheng Li
187
15
0
26 Feb 2024
Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation
Janvi Thakkar
Giulio Zizzo
S. Maffeis
AAML
150
0
0
18 Jan 2024
Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering
IEEE Symposium on Security and Privacy (IEEE S&P), 2023
Ce Feng
Nuo Xu
Wujie Wen
Parv Venkitasubramaniam
Caiwen Ding
249
7
0
25 Jul 2023
A Differentially Private Weighted Empirical Risk Minimization Procedure and its Application to Outcome Weighted Learning
S. Giddens
Yiwang Zhou
K. Krull
T. Brinkman
P. Song
Fan Liu
162
2
0
24 Jul 2023
Arbitrary Decisions are a Hidden Cost of Differentially Private Training
Conference on Fairness, Accountability and Transparency (FAccT), 2023
B. Kulynych
Hsiang Hsu
Carmela Troncoso
Flavio du Pin Calmon
348
26
0
28 Feb 2023
Advancements in Federated Learning: Models, Methods, and Privacy
ACM Computing Surveys (ACM Comput. Surv.), 2023
Hui Chen
Huandong Wang
Qingyue Long
Depeng Jin
Yong Li
FedML
427
33
0
22 Feb 2023
ReSQueing Parallel and Private Stochastic Convex Optimization
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2023
Y. Carmon
A. Jambulapati
Yujia Jin
Y. Lee
Daogao Liu
Aaron Sidford
Kevin Tian
FedML
390
19
0
01 Jan 2023
Differentially Private Tree-Based Redescription Mining
Data mining and knowledge discovery (DMKD), 2022
M. Mihelčić
Pauli Miettinen
223
1
0
13 Dec 2022
Memorization of Named Entities in Fine-tuned BERT Models
International Cross-Domain Conference on Machine Learning and Knowledge Extraction (CD-MAKE), 2022
Andor Diera
N. Lell
Aygul Garifullina
A. Scherp
213
2
0
07 Dec 2022
GRAIMATTER Green Paper: Recommendations for disclosure control of trained Machine Learning (ML) models from Trusted Research Environments (TREs)
E. Jefferson
J. Liley
Maeve Malone
S. Reel
Alba Crespi-Boixader
...
Christian Cole
F. Ritchie
A. Daly
Simon Rogers
Jim Q. Smith
199
9
0
03 Nov 2022
On the Statistical Complexity of Estimation and Testing under Privacy Constraints
Clément Lalanne
Aurélien Garivier
Rémi Gribonval
339
9
0
05 Oct 2022
Data Provenance via Differential Auditing
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
Xin Mu
Ming Pang
Feida Zhu
242
4
0
04 Sep 2022
Differentially Private Learning with Margin Guarantees
Neural Information Processing Systems (NeurIPS), 2022
Raef Bassily
M. Mohri
A. Suresh
209
10
0
21 Apr 2022
Private Convex Optimization via Exponential Mechanism
Annual Conference Computational Learning Theory (COLT), 2022
Sivakanth Gopi
Y. Lee
Daogao Liu
358
60
0
01 Mar 2022
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning
Proceedings of the IEEE (Proc. IEEE), 2022
Chuan Ma
Jun Li
Kang Wei
Bo Liu
Ming Ding
Long Yuan
Zhu Han
H. Vincent Poor
410
74
0
18 Feb 2022
Red Teaming Language Models with Language Models
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Ethan Perez
Saffron Huang
Francis Song
Trevor Cai
Roman Ring
John Aslanides
Amelia Glaese
Nat McAleese
G. Irving
AAML
543
930
0
07 Feb 2022
Differentially Private Ensemble Classifiers for Data Streams
Lovedeep Gondara
Ke Wang
Ricardo Silva Carvalho
FedML
112
4
0
09 Dec 2021
Differentially Private Sliced Wasserstein Distance
A. Rakotomamonjy
L. Ralaivola
207
24
0
05 Jul 2021
Adversarial Machine Learning for Cybersecurity and Computer Vision: Current Developments and Challenges
B. Xi
AAML
148
33
0
30 Jun 2021
Generalized Linear Bandits with Local Differential Privacy
Neural Information Processing Systems (NeurIPS), 2021
Yuxuan Han
Zhipeng Liang
Yang Wang
Jiheng Zhang
252
36
0
07 Jun 2021
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps
Janardhan Kulkarni
Y. Lee
Daogao Liu
247
32
0
29 Mar 2021
Robust Explanations for Private Support Vector Machines
R. Mochaourab
Sugandh Sinha
S. Greenstein
P. Papapetrou
105
4
0
07 Feb 2021
Robustness Threats of Differential Privacy
Nurislam Tursynbek
Aleksandr Petiushko
Ivan Oseledets
AAML
463
19
0
14 Dec 2020
Extracting Training Data from Large Language Models
USENIX Security Symposium (USENIX Security), 2020
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
Basel Alomair
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
1.3K
2,641
0
14 Dec 2020
Robust and Private Learning of Halfspaces
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Badih Ghazi
Ravi Kumar
Pasin Manurangsi
Thao Nguyen
255
12
0
30 Nov 2020
When Machine Learning Meets Privacy: A Survey and Outlook
ACM Computing Surveys (ACM CSUR), 2020
B. Liu
Ming Ding
Sina shaham
W. Rahayu
F. Farokhi
Zihuai Lin
292
332
0
24 Nov 2020
Privacy Preservation in Federated Learning: An insightful survey from the GDPR Perspective
N. Truong
Kai Sun
Siyao Wang
Florian Guitton
Wenhan Luo
FedML
347
10
0
10 Nov 2020
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning
Network and Distributed System Security Symposium (NDSS), 2020
Mohammad Naseri
Jamie Hayes
Emiliano De Cristofaro
FedML
356
205
0
08 Sep 2020
A(DP)
2
^2
2
SGD: Asynchronous Decentralized Parallel Stochastic Gradient Descent with Differential Privacy
Jie Xu
Wei Zhang
Haiwei Yang
FedML
148
12
0
21 Aug 2020
Trustworthy AI Inference Systems: An Industry Research View
Rosario Cammarota
M. Schunter
Anand Rajan
Fabian Boemer
Ágnes Kiss
...
Aydin Aysu
Fateme S. Hosseini
Chengmo Yang
Eric Wallace
Pam Norton
260
17
0
10 Aug 2020
Differentially Private Accelerated Optimization Algorithms
Nurdan Kuru
cS. .Ilker Birbil
Mert Gurbuzbalaban
S. Yıldırım
207
26
0
05 Aug 2020
Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context
Ehsan Toreini
Mhairi Aitken
Kovila P. L. Coopamootoo
Karen Elliott
Vladimiro González-Zelaya
P. Missier
Magdalene Ng
Aad van Moorsel
338
19
0
17 Jul 2020
Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent
Lauren Watson
Benedek Rozemberczki
Rik Sarkar
191
1
0
25 Jun 2020
Differentially Private Convex Optimization with Feasibility Guarantees
V. Dvorkin
Ferdinando Fioretto
Pascal Van Hentenryck
J. Kazempour
Pierre Pinson
157
6
0
22 Jun 2020
Upper Bounds on the Generalization Error of Private Algorithms for Discrete Data
Borja Rodríguez Gálvez
Germán Bassi
Mikael Skoglund
287
9
0
12 May 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
David Enthoven
Zaid Al-Ars
FedML
191
59
0
01 Apr 2020
Differentially Private Naive Bayes Classifier using Smooth Sensitivity
Proceedings on Privacy Enhancing Technologies (PoPETs), 2020
Farzad Zafarani
Chris Clifton
203
11
0
31 Mar 2020
Corella: A Private Multi Server Learning Approach based on Correlated Queries
H. Ehteram
M. Maddah-ali
Mahtab Mirmohseni
182
0
0
26 Mar 2020
Privacy-Preserving Public Release of Datasets for Support Vector Machine Classification
IEEE Transactions on Big Data (IEEE Trans. Big Data), 2019
F. Farokhi
139
10
0
29 Dec 2019
SoK: Chasing Accuracy and Privacy, and Catching Both in Differentially Private Histogram Publication
Boel Nelson
Jenni Reuben
230
5
0
30 Oct 2019
Differentially Private Distributed Data Summarization under Covariate Shift
Neural Information Processing Systems (NeurIPS), 2019
Kanthi Kiran Sarpatwar
Karthikeyan Shanmugam
Venkata Sitaramagiridharganesh Ganapavarapu
A. Jagmohan
Roman Vaculin
114
10
0
28 Oct 2019
Real-World Image Datasets for Federated Learning
Jiahuan Luo
Xueyang Wu
Yu Luo
Anbu Huang
Yunfeng Huang
Yang Liu
Qiang Yang
FedML
204
108
0
14 Oct 2019
Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey
Bin Qian
Jie Su
Z. Wen
D. N. Jha
Yinhao Li
...
Albert Y. Zomaya
Omer F. Rana
Lizhe Wang
Maciej Koutny
R. Ranjan
307
4
0
11 Oct 2019
Differentially Private Regression and Classification with Sparse Gaussian Processes
Journal of machine learning research (JMLR), 2019
M. Smith
Mauricio A. Alvarez
Neil D. Lawrence
112
6
0
19 Sep 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
241
433
0
29 Aug 2019
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