Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2002.09463
Cited By
v1
v2 (latest)
Privately Learning Markov Random Fields
International Conference on Machine Learning (ICML), 2020
21 February 2020
Huanyu Zhang
Gautam Kamath
Janardhan Kulkarni
Zhiwei Steven Wu
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Privately Learning Markov Random Fields"
21 / 21 papers shown
Estimating Ising Models in Total Variation Distance
C. Daskalakis
Vardis Kandiros
Rui-Min Yao
221
0
0
26 Nov 2025
Learning the Sherrington-Kirkpatrick Model Even at Low Temperature
Symposium on the Theory of Computing (STOC), 2024
Gautam Chandrasekaran
Adam R. Klivans
292
2
0
17 Nov 2024
PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model
Abhinav Chakraborty
Anirban Chatterjee
Abhinandan Dalal
253
0
0
29 Jan 2024
A Unified Approach to Learning Ising Models: Beyond Independence and Bounded Width
Symposium on the Theory of Computing (STOC), 2023
Jason Gaitonde
Elchanan Mossel
275
11
0
15 Nov 2023
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions
International Conference on Algorithmic Learning Theory (ALT), 2023
Vikrant Singhal
627
10
0
13 Apr 2023
Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning
Tianxi Cai
Yichen Wang
Linjun Zhang
280
24
0
13 Mar 2023
Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions
Neural Information Processing Systems (NeurIPS), 2022
Omri Ben-Eliezer
Dan Mikulincer
Ilias Zadik
FedML
328
8
0
15 Aug 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
Private Robust Estimation by Stabilizing Convex Relaxations
Pravesh Kothari
Pasin Manurangsi
A. Velingker
273
51
0
07 Dec 2021
Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism
Samuel B. Hopkins
Gautam Kamath
Mahbod Majid
FedML
334
68
0
25 Nov 2021
A Private and Computationally-Efficient Estimator for Unbounded Gaussians
Gautam Kamath
Argyris Mouzakis
Vikrant Singhal
Thomas Steinke
Jonathan R. Ullman
360
44
0
08 Nov 2021
Prior-Aware Distribution Estimation for Differential Privacy
Yuchao Tao
Johes Bater
Ashwin Machanavajjhala
264
1
0
09 Jun 2021
Privately Learning Mixtures of Axis-Aligned Gaussians
Neural Information Processing Systems (NeurIPS), 2021
Ishaq Aden-Ali
H. Ashtiani
Christopher Liaw
FedML
209
14
0
03 Jun 2021
Robust and Differentially Private Mean Estimation
Neural Information Processing Systems (NeurIPS), 2021
Xiyang Liu
Weihao Kong
Sham Kakade
Sewoong Oh
OOD
FedML
341
84
0
18 Feb 2021
Optimal Private Median Estimation under Minimal Distributional Assumptions
Neural Information Processing Systems (NeurIPS), 2020
Christos Tzamos
Emmanouil-Vasileios Vlatakis-Gkaragkounis
Ilias Zadik
269
24
0
12 Nov 2020
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds
T. Tony Cai
Yichen Wang
Linjun Zhang
FedML
297
23
0
08 Nov 2020
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians
International Conference on Algorithmic Learning Theory (ALT), 2020
Ishaq Aden-Ali
H. Ashtiani
Gautam Kamath
458
48
0
19 Oct 2020
CoinPress: Practical Private Mean and Covariance Estimation
Neural Information Processing Systems (NeurIPS), 2020
Sourav Biswas
Yihe Dong
Gautam Kamath
Jonathan R. Ullman
351
128
0
11 Jun 2020
A Primer on Private Statistics
Gautam Kamath
Jonathan R. Ullman
292
56
0
30 Apr 2020
Differentially Private Assouad, Fano, and Le Cam
International Conference on Algorithmic Learning Theory (ALT), 2020
Jayadev Acharya
Ziteng Sun
Huanyu Zhang
FedML
450
70
0
14 Apr 2020
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models
International Conference on Machine Learning (ICML), 2019
Amrita Roy Chowdhury
Theodoros Rekatsinas
S. Jha
341
11
0
30 May 2019
1
Page 1 of 1
