Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem

22 February 2018

Papers citing "Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem"

11 / 61 papers shown

Title
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness Murat A. Erdogdu Rasa Hosseinzadeh 16 75 0 27 May 2020
Self-Paced Deep Reinforcement Learning Pascal Klink Carlo DÉramo Jan Peters Joni Pajarinen ODL 43 54 0 24 Apr 2020
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry Andre Wibisono 82 49 0 04 Nov 2019
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates Adil Salim D. Kovalev Peter Richtárik 14 25 0 28 May 2019
Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions Zongchen Chen Santosh Vempala 26 64 0 07 May 2019
Understanding MCMC Dynamics as Flows on the Wasserstein Space Chang-Shu Liu Jingwei Zhuo Jun Zhu 21 22 0 01 Feb 2019
Sampling Can Be Faster Than Optimization Yian Ma Yuansi Chen Chi Jin Nicolas Flammarion Michael I. Jordan 27 183 0 20 Nov 2018
Langevin Monte Carlo and JKO splitting Espen Bernton 15 78 0 23 Feb 2018
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 40 159 0 21 Oct 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark Schmidt 139 1,205 0 16 Aug 2016
MCMC using Hamiltonian dynamics Radford M. Neal 189 3,268 0 09 Jun 2012