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1802.04085
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Empirical Risk Minimization in Non-interactive Local Differential Privacy: Efficiency and High Dimensional Case
12 February 2018
Haiyan Zhao
Marco Gaboardi
Jinhui Xu
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Papers citing
"Empirical Risk Minimization in Non-interactive Local Differential Privacy: Efficiency and High Dimensional Case"
28 / 28 papers shown
Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via
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f
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-Differential Privacy
Xiang Li
Buxin Su
Chendi Wang
Qi Long
Weijie J. Su
FedML
240
4
0
22 Oct 2025
Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition
Difei Xu
Meng Ding
Zihang Xiang
Jinhui Xu
Haiyan Zhao
244
2
0
04 Sep 2025
Bipartite Randomized Response Mechanism for Local Differential Privacy
Shun Zhang
Hai Zhu
Zhili Chen
N. Xiong
355
0
0
29 Apr 2025
Distributed Differentially Private Data Analytics via Secure Sketching
IACR Cryptology ePrint Archive (IACR ePrint), 2024
Jakob Burkhardt
Hannah Keller
Claudio Orlandi
Chris Schwiegelshohn
FedML
470
1
0
30 Nov 2024
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards
International Conference on Machine Learning (ICML), 2023
Yulian Wu
Xingyu Zhou
Sayak Ray Chowdhury
Haiyan Zhao
427
4
0
01 Jun 2023
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened
Proceedings of the VLDB Endowment (PVLDB), 2023
Shaowei Wang
FedML
638
14
0
11 Apr 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions
Findings (Findings), 2023
Lijie Hu
Ivan Habernal
Lei Shen
Haiyan Zhao
AAML
323
26
0
22 Jan 2023
On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data
Asian Conference on Machine Learning (ACML), 2022
Jinyan Su
Jinhui Xu
Haiyan Zhao
326
2
0
17 Sep 2022
Practical Vertical Federated Learning with Unsupervised Representation Learning
IEEE Transactions on Big Data (TBD), 2022
Zhaomin Wu
Yue Liu
Bingsheng He
FedML
235
59
0
13 Aug 2022
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging
Neural Information Processing Systems (NeurIPS), 2022
Edwige Cyffers
Mathieu Even
A. Bellet
Laurent Massoulié
FedML
527
32
0
10 Jun 2022
One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Hajime Ono
Kazuhiro Minami
H. Hino
165
1
0
15 Feb 2022
Faster Rates of Private Stochastic Convex Optimization
Jinyan Su
Lijie Hu
Haiyan Zhao
271
14
0
31 Jul 2021
Locally private online change point detection
Neural Information Processing Systems (NeurIPS), 2021
Thomas B. Berrett
Yi Yu
316
16
0
22 May 2021
Privacy Amplification by Decentralization
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Edwige Cyffers
A. Bellet
FedML
592
46
0
09 Dec 2020
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy
Journal of machine learning research (JMLR), 2020
Haiyan Zhao
Marco Gaboardi
Adam D. Smith
Jinhui Xu
228
22
0
11 Nov 2020
Strongly universally consistent nonparametric regression and classification with privatised data
Electronic Journal of Statistics (EJS), 2020
Thomas B. Berrett
László Gyorfi
Harro Walk
265
19
0
31 Oct 2020
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data
Haiyan Zhao
Hanshen Xiao
S. Devadas
Jinhui Xu
260
67
0
21 Oct 2020
A Comprehensive Survey on Local Differential Privacy Toward Data Statistics and Analysis
Italian National Conference on Sensors (INS), 2020
Teng Wang
Xuefeng Zhang
Xuefeng Zhang
Xinyu Yang
376
110
0
11 Oct 2020
Local Differential Privacy and Its Applications: A Comprehensive Survey
Mengmeng Yang
Lingjuan Lyu
Jun Zhao
Tianqing Zhu
Kwok-Yan Lam
315
194
0
09 Aug 2020
Distributionally-Robust Machine Learning Using Locally Differentially-Private Data
Optimization Letters (Optim. Lett.), 2020
F. Farokhi
FedML
OOD
327
11
0
24 Jun 2020
Locally Differentially Private (Contextual) Bandits Learning
Neural Information Processing Systems (NeurIPS), 2020
Kai Zheng
Tianle Cai
Weiran Huang
Zhenguo Li
Liwei Wang
429
69
0
01 Jun 2020
Input Perturbation: A New Paradigm between Central and Local Differential Privacy
Yilin Kang
Yong Liu
Ben Niu
Xin-Yi Tong
Likun Zhang
Weiping Wang
228
15
0
20 Feb 2020
Wireless Federated Learning with Local Differential Privacy
International Symposium on Information Theory (ISIT), 2020
Mohamed Seif
Ravi Tandon
Ming Li
273
197
0
12 Feb 2020
A Knowledge Transfer Framework for Differentially Private Sparse Learning
AAAI Conference on Artificial Intelligence (AAAI), 2019
Lingxiao Wang
Quanquan Gu
FedML
161
15
0
13 Sep 2019
Locally Differentially Private Data Collection and Analysis
Teng Wang
Jun Zhao
Xinyu Yang
Xuebin Ren
203
13
0
05 Jun 2019
Differentially Private High Dimensional Sparse Covariance Matrix Estimation
Haiyan Zhao
Jinhui Xu
293
11
0
18 Jan 2019
Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations
Haiyan Zhao
Adam D. Smith
Jinhui Xu
267
24
0
17 Dec 2018
Locally Differentially Private Heavy Hitter Identification
Tianhao Wang
Ninghui Li
S. Jha
247
131
0
22 Aug 2017
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