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2011.03900
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The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds
8 November 2020
T. Tony Cai
Yichen Wang
Linjun Zhang
FedML
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Papers citing
"The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds"
13 / 13 papers shown
Differentially Private Sparse Linear Regression with Heavy-tailed Responses
Xizhi Tian
Meng Ding
Touming Tao
Zihang Xiang
Di Wang
226
2
0
07 Jun 2025
Differentially Private High Dimensional Bandits
Apurv Shukla
227
0
0
06 Feb 2024
Truthful Generalized Linear Models
Workshop on Internet and Network Economics (WINE), 2022
Yuan Qiu
Jinyan Liu
Haiyan Zhao
FedML
319
3
0
16 Sep 2022
Fast Composite Optimization and Statistical Recovery in Federated Learning
International Conference on Machine Learning (ICML), 2022
Yajie Bao
M. Crawshaw
Sha Luo
Mingrui Liu
FedML
257
20
0
17 Jul 2022
Hypothesis Testing for Differentially Private Linear Regression
Neural Information Processing Systems (NeurIPS), 2022
Daniel Alabi
Salil P. Vadhan
FedML
202
16
0
29 Jun 2022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma
Neural Information Processing Systems (NeurIPS), 2022
Gautam Kamath
Argyris Mouzakis
Vikrant Singhal
FedML
534
36
0
17 May 2022
Differentially Private Regression with Unbounded Covariates
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Jason Milionis
Alkis Kalavasis
Eleni Psaroudaki
Stratis Ioannidis
217
13
0
19 Feb 2022
Faster Rates of Private Stochastic Convex Optimization
Jinyan Su
Lijie Hu
Haiyan Zhao
269
14
0
31 Jul 2021
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data
ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS), 2021
Lijie Hu
Shuo Ni
Hanshen Xiao
Haiyan Zhao
348
61
0
23 Jul 2021
High-Dimensional Differentially-Private EM Algorithm: Methods and Near-Optimal Statistical Guarantees
Zhe Zhang
Linjun Zhang
FedML
274
3
0
01 Apr 2021
Differentially private inference via noisy optimization
Annals of Statistics (Ann. Stat.), 2021
Marco Avella-Medina
Casey Bradshaw
Po-Ling Loh
FedML
540
37
0
19 Mar 2021
A Central Limit Theorem for Differentially Private Query Answering
Neural Information Processing Systems (NeurIPS), 2021
Jinshuo Dong
Weijie J. Su
Linjun Zhang
205
20
0
15 Mar 2021
Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data
Journal of machine learning research (JMLR), 2019
Haiyan Zhao
Lijie Hu
Huanyu Zhang
Marco Gaboardi
Jinhui Xu
520
11
0
01 Oct 2019
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