Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities

15 December 2018

Papers citing "Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities"

18 / 18 papers shown

Title
Estimating Normalizing Constants for Log-Concave Distributions: Algorithms and Lower Bounds Rong Ge Holden Lee Jianfeng Lu 35 22 0 08 Nov 2019
On sampling from a log-concave density using kinetic Langevin diffusions A. Dalalyan L. Riou-Durand 58 154 0 24 Jul 2018
Sharp convergence rates for Langevin dynamics in the nonconvex setting Xiang Cheng Niladri S. Chatterji Yasin Abbasi-Yadkori Peter L. Bartlett Michael I. Jordan 45 166 0 04 May 2018
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo Niladri S. Chatterji Nicolas Flammarion Yian Ma Peter L. Bartlett Michael I. Jordan 41 87 0 15 Feb 2018
Log-concave sampling: Metropolis-Hastings algorithms are fast Raaz Dwivedi Yuansi Chen Martin J. Wainwright Bin Yu 63 253 0 08 Jan 2018
Convergence Rate of Riemannian Hamiltonian Monte Carlo and Faster Polytope Volume Computation Y. Lee Santosh Vempala 53 113 0 17 Oct 2017
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient A. Dalalyan Avetik G. Karagulyan 60 296 0 29 Sep 2017
A Convergence Analysis for A Class of Practical Variance-Reduction Stochastic Gradient MCMC Changyou Chen Wenlin Wang Yizhe Zhang Qinliang Su Lawrence Carin 41 28 0 04 Sep 2017
Rapid Mixing of Hamiltonian Monte Carlo on Strongly Log-Concave Distributions Oren Mangoubi Aaron Smith 97 106 0 23 Aug 2017
Underdamped Langevin MCMC: A non-asymptotic analysis Xiang Cheng Niladri S. Chatterji Peter L. Bartlett Michael I. Jordan 82 296 0 12 Jul 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 49 101 0 16 Jun 2017
Relative Error Tensor Low Rank Approximation Zhao Song David P. Woodruff Peilin Zhong 48 123 0 26 Apr 2017
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics Yuchen Zhang Percy Liang Moses Charikar 43 234 0 18 Feb 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 62 518 0 13 Feb 2017
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 67 232 0 11 Jul 2016
High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 74 352 0 05 May 2016
Theoretical guarantees for approximate sampling from smooth and log-concave densities A. Dalalyan 63 514 0 23 Dec 2014
Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression Francis R. Bach 65 164 0 25 Mar 2013