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Privately Learning High-Dimensional Distributions

Privately Learning High-Dimensional Distributions

1 May 2018
Gautam Kamath
Jerry Li
Vikrant Singhal
Jonathan R. Ullman
    FedML
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Papers citing "Privately Learning High-Dimensional Distributions"

32 / 32 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
35
2
0
19 Aug 2024
On Differentially Private U Statistics
On Differentially Private U Statistics
Kamalika Chaudhuri
Po-Ling Loh
Shourya Pandey
Purnamrita Sarkar
FedML
54
0
0
06 Jul 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
36
0
0
09 Dec 2023
Instance-Specific Asymmetric Sensitivity in Differential Privacy
Instance-Specific Asymmetric Sensitivity in Differential Privacy
David Durfee
19
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
35
11
0
11 Aug 2023
Score Attack: A Lower Bound Technique for Optimal Differentially Private
  Learning
Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning
T. Tony Cai
Yichen Wang
Linjun Zhang
39
16
0
13 Mar 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
On Private and Robust Bandits
On Private and Robust Bandits
Yulian Wu
Xingyu Zhou
Youming Tao
Di Wang
10
5
0
06 Feb 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
19
15
0
17 Jan 2023
DP-SIPS: A simpler, more scalable mechanism for differentially private
  partition selection
DP-SIPS: A simpler, more scalable mechanism for differentially private partition selection
Marika Swanberg
Damien Desfontaines
Samuel Haney
24
6
0
05 Jan 2023
Private Estimation with Public Data
Private Estimation with Public Data
Alex Bie
Gautam Kamath
Vikrant Singhal
28
28
0
16 Aug 2022
Measuring Forgetting of Memorized Training Examples
Measuring Forgetting of Memorized Training Examples
Matthew Jagielski
Om Thakkar
Florian Tramèr
Daphne Ippolito
Katherine Lee
...
Eric Wallace
Shuang Song
Abhradeep Thakurta
Nicolas Papernot
Chiyuan Zhang
TDI
40
102
0
30 Jun 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
31
26
0
17 May 2022
Private High-Dimensional Hypothesis Testing
Private High-Dimensional Hypothesis Testing
Shyam Narayanan
FedML
25
11
0
03 Mar 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
Provably Private Distributed Averaging Consensus: An
  Information-Theoretic Approach
Provably Private Distributed Averaging Consensus: An Information-Theoretic Approach
Mohammad Fereydounian
Aryan Mokhtari
Ramtin Pedarsani
Hamed Hassani
FedML
19
2
0
18 Feb 2022
Optimal and Differentially Private Data Acquisition: Central and Local
  Mechanisms
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms
Alireza Fallah
A. Makhdoumi
Azarakhsh Malekian
Asuman Ozdaglar
FedML
21
29
0
10 Jan 2022
Differential Privacy Over Riemannian Manifolds
Differential Privacy Over Riemannian Manifolds
M. Reimherr
Karthik Bharath
Carlos Soto
23
17
0
03 Nov 2021
Tight and Robust Private Mean Estimation with Few Users
Tight and Robust Private Mean Estimation with Few Users
Cheng-Han Chiang
Vahab Mirrokni
Hung-yi Lee
FedML
28
28
0
22 Oct 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
Covariance-Aware Private Mean Estimation Without Private Covariance
  Estimation
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation
Gavin Brown
Marco Gaboardi
Adam D. Smith
Jonathan R. Ullman
Lydia Zakynthinou
FedML
21
48
0
24 Jun 2021
Optimal Private Median Estimation under Minimal Distributional
  Assumptions
Optimal Private Median Estimation under Minimal Distributional Assumptions
Christos Tzamos
Emmanouil-Vasileios Vlatakis-Gkaragkounis
Ilias Zadik
14
21
0
12 Nov 2020
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax
  Lower Bounds
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds
T. Tony Cai
Yichen Wang
Linjun Zhang
FedML
30
20
0
08 Nov 2020
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
37
41
0
19 Oct 2020
Learning discrete distributions: user vs item-level privacy
Learning discrete distributions: user vs item-level privacy
Yuhan Liu
A. Suresh
Felix X. Yu
Sanjiv Kumar
Michael Riley
FedML
25
52
0
27 Jul 2020
CoinPress: Practical Private Mean and Covariance Estimation
CoinPress: Practical Private Mean and Covariance Estimation
Sourav Biswas
Yihe Dong
Gautam Kamath
Jonathan R. Ullman
26
113
0
11 Jun 2020
A Primer on Private Statistics
A Primer on Private Statistics
Gautam Kamath
Jonathan R. Ullman
33
48
0
30 Apr 2020
Differentially Private Assouad, Fano, and Le Cam
Differentially Private Assouad, Fano, and Le Cam
Jayadev Acharya
Ziteng Sun
Huanyu Zhang
FedML
18
57
0
14 Apr 2020
Average-Case Averages: Private Algorithms for Smooth Sensitivity and
  Mean Estimation
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
Mark Bun
Thomas Steinke
34
74
0
06 Jun 2019
Private Identity Testing for High-Dimensional Distributions
Private Identity Testing for High-Dimensional Distributions
C. Canonne
Gautam Kamath
Audra McMillan
Jonathan R. Ullman
Lydia Zakynthinou
30
36
0
28 May 2019
Locally Private Gaussian Estimation
Locally Private Gaussian Estimation
Matthew Joseph
Janardhan Kulkarni
Jieming Mao
Zhiwei Steven Wu
FedML
29
38
0
20 Nov 2018
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit
  and Independence Testing
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing
Marco Gaboardi
H. Lim
Ryan M. Rogers
Salil P. Vadhan
45
137
0
07 Feb 2016
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