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Private and polynomial time algorithms for learning Gaussians and beyond

Private and polynomial time algorithms for learning Gaussians and beyond

22 November 2021
H. Ashtiani
Christopher Liaw
ArXivPDFHTML

Papers citing "Private and polynomial time algorithms for learning Gaussians and beyond"

19 / 19 papers shown
Title
Private Means and the Curious Incident of the Free Lunch
Private Means and the Curious Incident of the Free Lunch
Jack Fitzsimons
James Honaker
Michael Shoemate
Vikrant Singhal
46
2
0
19 Aug 2024
Sample-Optimal Locally Private Hypothesis Selection and the Provable
  Benefits of Interactivity
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity
A. F. Pour
Hassan Ashtiani
S. Asoodeh
41
0
0
09 Dec 2023
Instance-Specific Asymmetric Sensitivity in Differential Privacy
Instance-Specific Asymmetric Sensitivity in Differential Privacy
David Durfee
32
1
0
02 Nov 2023
Private Distribution Learning with Public Data: The View from Sample
  Compression
Private Distribution Learning with Public Data: The View from Sample Compression
Shai Ben-David
Alex Bie
C. Canonne
Gautam Kamath
Vikrant Singhal
42
11
0
11 Aug 2023
A Polynomial Time, Pure Differentially Private Estimator for Binary
  Product Distributions
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions
Vikrant Singhal
34
9
0
13 Apr 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture
  Models
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models
Jamil Arbas
H. Ashtiani
Christopher Liaw
40
23
0
07 Mar 2023
Near Optimal Private and Robust Linear Regression
Near Optimal Private and Robust Linear Regression
Xiyang Liu
Prateek Jain
Weihao Kong
Sewoong Oh
A. Suggala
41
9
0
30 Jan 2023
A Fast Algorithm for Adaptive Private Mean Estimation
A Fast Algorithm for Adaptive Private Mean Estimation
John C. Duchi
Saminul Haque
Rohith Kuditipudi
FedML
24
15
0
17 Jan 2023
Private estimation algorithms for stochastic block models and mixture
  models
Private estimation algorithms for stochastic block models and mixture models
Hongjie Chen
Vincent Cohen-Addad
Tommaso dÓrsi
Alessandro Epasto
Jacob Imola
David Steurer
Stefan Tiegel
FedML
43
20
0
11 Jan 2023
Robustness Implies Privacy in Statistical Estimation
Robustness Implies Privacy in Statistical Estimation
Samuel B. Hopkins
Gautam Kamath
Mahbod Majid
Shyam Narayanan
18
49
0
09 Dec 2022
Private Estimation with Public Data
Private Estimation with Public Data
Alex Bie
Gautam Kamath
Vikrant Singhal
36
28
0
16 Aug 2022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting
  Lemma
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma
Gautam Kamath
Argyris Mouzakis
Vikrant Singhal
FedML
42
26
0
17 May 2022
Differentially Private Regression with Unbounded Covariates
Differentially Private Regression with Unbounded Covariates
Jason Milionis
Alkis Kalavasis
Dimitris Fotakis
Stratis Ioannidis
23
10
0
19 Feb 2022
Private Robust Estimation by Stabilizing Convex Relaxations
Private Robust Estimation by Stabilizing Convex Relaxations
Pravesh Kothari
Pasin Manurangsi
A. Velingker
32
45
0
07 Dec 2021
A Private and Computationally-Efficient Estimator for Unbounded
  Gaussians
A Private and Computationally-Efficient Estimator for Unbounded Gaussians
Gautam Kamath
Argyris Mouzakis
Vikrant Singhal
Thomas Steinke
Jonathan R. Ullman
55
39
0
08 Nov 2021
FriendlyCore: Practical Differentially Private Aggregation
FriendlyCore: Practical Differentially Private Aggregation
Eliad Tsfadia
E. Cohen
Haim Kaplan
Yishay Mansour
Uri Stemmer
20
33
0
19 Oct 2021
Robust and Differentially Private Mean Estimation
Robust and Differentially Private Mean Estimation
Xiyang Liu
Weihao Kong
Sham Kakade
Sewoong Oh
OOD
FedML
53
75
0
18 Feb 2021
On the Sample Complexity of Privately Learning Unbounded
  High-Dimensional Gaussians
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians
Ishaq Aden-Ali
H. Ashtiani
Gautam Kamath
40
41
0
19 Oct 2020
Privately Learning High-Dimensional Distributions
Privately Learning High-Dimensional Distributions
Gautam Kamath
Jerry Li
Vikrant Singhal
Jonathan R. Ullman
FedML
69
148
0
01 May 2018
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