Sampling from Log-Concave Distributions with Infinity-Distance Guarantees

7 November 2021

Papers citing "Sampling from Log-Concave Distributions with Infinity-Distance Guarantees"

8 / 8 papers shown

Title
Purifying Approximate Differential Privacy with Randomized Post-processing Yingyu Lin Erchi Wang Yi-An Ma Yu-Xiang Wang 34 0 0 27 Mar 2025
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy Yingyu Lin Yian Ma Yu-Xiang Wang Rachel Redberg Zhiqi Bu 33 4 0 23 Oct 2023
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation Kristian Georgiev Samuel B. Hopkins FedML 33 21 0 01 Nov 2022
Private Matrix Approximation and Geometry of Unitary Orbits Oren Mangoubi Yikai Wu Satyen Kale Abhradeep Thakurta Nisheeth K. Vishnoi 17 3 0 06 Jul 2022
Sampling from Log-Concave Distributions over Polytopes via a Soft-Threshold Dikin Walk Oren Mangoubi Nisheeth K. Vishnoi 74 2 0 19 Jun 2022
Differentially Private Sampling from Rashomon Sets, and the Universality of Langevin Diffusion for Convex Optimization Arun Ganesh Abhradeep Thakurta Jalaj Upadhyay 26 1 0 04 Apr 2022
Private Convex Optimization via Exponential Mechanism Sivakanth Gopi Y. Lee Daogao Liu 83 52 0 01 Mar 2022
Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism Samuel B. Hopkins Gautam Kamath Mahbod Majid FedML 30 60 0 25 Nov 2021