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A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for
  Proximal Samplers

A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers

27 May 2024
Ye He
Alireza Mousavi-Hosseini
Krishnakumar Balasubramanian
Murat A. Erdogdu
ArXiv (abs)PDFHTML

Papers citing "A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers"

16 / 16 papers shown
Title
Weak Poincaré Inequalities for Markov chains: theory and applications
Weak Poincaré Inequalities for Markov chains: theory and applications
Christophe Andrieu
Anthony Lee
Samuel Power
Andi Q. Wang
22
4
0
18 Dec 2023
A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm
  under Smoothness and Isoperimetry
A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry
Yuansi Chen
Khashayar Gatmiry
56
6
0
08 Apr 2023
Fisher information lower bounds for sampling
Fisher information lower bounds for sampling
Sinho Chewi
P. Gerber
Holden Lee
Chen Lu
93
15
0
05 Oct 2022
Improved analysis for a proximal algorithm for sampling
Improved analysis for a proximal algorithm for sampling
Yongxin Chen
Sinho Chewi
Adil Salim
Andre Wibisono
100
58
0
13 Feb 2022
Optimal dimension dependence of the Metropolis-Adjusted Langevin
  Algorithm
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm
Sinho Chewi
Chen Lu
Kwangjun Ahn
Xiang Cheng
Thibaut Le Gouic
Philippe Rigollet
67
66
0
23 Dec 2020
Structured Logconcave Sampling with a Restricted Gaussian Oracle
Structured Logconcave Sampling with a Restricted Gaussian Oracle
Y. Lee
Ruoqi Shen
Kevin Tian
56
72
0
07 Oct 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail
  Growth and Smoothness
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness
Murat A. Erdogdu
Rasa Hosseinzadeh
62
76
0
27 May 2020
Learning Halfspaces with Massart Noise Under Structured Distributions
Learning Halfspaces with Massart Noise Under Structured Distributions
Ilias Diakonikolas
Vasilis Kontonis
Christos Tzamos
Nikos Zarifis
51
61
0
13 Feb 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized
  Hamiltonian Monte Carlo
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo
Y. Lee
Ruoqi Shen
Kevin Tian
52
37
0
10 Feb 2020
Estimating Normalizing Constants for Log-Concave Distributions:
  Algorithms and Lower Bounds
Estimating Normalizing Constants for Log-Concave Distributions: Algorithms and Lower Bounds
Rong Ge
Holden Lee
Jianfeng Lu
53
22
0
08 Nov 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
Xuechen Li
Denny Wu
Lester W. Mackey
Murat A. Erdogdu
52
71
0
19 Jun 2019
Global Non-convex Optimization with Discretized Diffusions
Global Non-convex Optimization with Discretized Diffusions
Murat A. Erdogdu
Lester W. Mackey
Ohad Shamir
69
105
0
29 Oct 2018
Underdamped Langevin MCMC: A non-asymptotic analysis
Underdamped Langevin MCMC: A non-asymptotic analysis
Xiang Cheng
Niladri S. Chatterji
Peter L. Bartlett
Michael I. Jordan
89
301
0
12 Jul 2017
Exponential Ergodicity of the Bouncy Particle Sampler
Exponential Ergodicity of the Bouncy Particle Sampler
George Deligiannidis
Alexandre Bouchard-Côté
Arnaud Doucet
70
49
0
12 May 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a
  nonasymptotic analysis
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis
Maxim Raginsky
Alexander Rakhlin
Matus Telgarsky
73
521
0
13 Feb 2017
Non-asymptotic convergence analysis for the Unadjusted Langevin
  Algorithm
Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm
Alain Durmus
Eric Moulines
69
414
0
17 Jul 2015
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