Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms

8 June 2022

Papers citing "Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms"

8 / 8 papers shown

Title
Beyond Propagation of Chaos: A Stochastic Algorithm for Mean Field Optimization Chandan Tankala Dheeraj M. Nagaraj Anant Raj 34 0 0 17 Mar 2025
The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models S. Kandasamy Dheeraj M. Nagaraj DiffM 16 2 0 27 May 2024
Faster Sampling via Stochastic Gradient Proximal Sampler Xunpeng Huang Difan Zou Yian Ma Hanze Dong Tong Zhang 49 3 0 27 May 2024
Convergence of mean-field Langevin dynamics: Time and space discretization, stochastic gradient, and variance reduction Taiji Suzuki Denny Wu Atsushi Nitanda 17 16 0 12 Jun 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 17 7 0 27 May 2023
Fisher information lower bounds for sampling Sinho Chewi P. Gerber Holden Lee Chen Lu 35 15 0 05 Oct 2022
Private Convex Optimization via Exponential Mechanism Sivakanth Gopi Y. Lee Daogao Liu 65 51 0 01 Mar 2022
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling Difan Zou Pan Xu Quanquan Gu 31 35 0 19 Oct 2020