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Is There an Analog of Nesterov Acceleration for MCMC?

4 February 2019

Niladri Chatterji

Papers citing "Is There an Analog of Nesterov Acceleration for MCMC?"

50 / 55 papers shown

Title
An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling Xunpeng Huang Hanze Dong Difan Zou Tong Zhang 72 0 0 10 Mar 2024
Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection Kush S. Bhatia Nikki Lijing Kuang Yi-An Ma Yixin Wang 50 7 0 22 Jul 2022
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time Jun-Kun Wang Andre Wibisono 97 9 0 05 Jul 2022
Federated Learning with a Sampling Algorithm under Isoperimetry Lukang Sun Adil Salim Peter Richtárik FedML 92 7 0 02 Jun 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 88 19 0 01 Jun 2022
Particle algorithms for maximum likelihood training of latent variable models Juan Kuntz Jen Ning Lim A. M. Johansen FedML 109 23 0 27 Apr 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents Alessandro Barp Lancelot Da Costa G. Francca Karl J. Friston Mark Girolami Michael I. Jordan G. Pavliotis 97 25 0 20 Mar 2022
HMC and underdamped Langevin united in the unadjusted convex smooth case Nicolai Gouraud Pierre Le Bris Adrien Majka Pierre Monmarché 82 12 0 02 Feb 2022
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion Tim Dockhorn Arash Vahdat Karsten Kreis DiffM 113 237 0 14 Dec 2021
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi-An Ma Zhao Song Guang Lin FedML 82 17 0 09 Dec 2021
De-randomizing MCMC dynamics with the diffusion Stein operator Zheyan Shen Markus Heinonen Samuel Kaski DiffM 40 4 0 07 Oct 2021
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi-An Ma Tong Zhang 72 16 0 05 Oct 2021
Universal Approximation for Log-concave Distributions using Well-conditioned Normalizing Flows Holden Lee Chirag Pabbaraju A. Sevekari Andrej Risteski 66 8 0 07 Jul 2021
Sampling with Mirrored Stein Operators Jiaxin Shi Chang-rui Liu Lester W. Mackey 128 19 0 23 Jun 2021
A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1 Adil Salim Lukang Sun Peter Richtárik 74 20 0 06 Jun 2021
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 72 17 0 06 May 2021
Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-Differentiable Priors Jacob Vorstrup Goldman Torben Sell Sumeetpal S. Singh 46 8 0 16 Mar 2021
Projected Wasserstein gradient descent for high-dimensional Bayesian inference Yifei Wang Peng Chen Wuchen Li 77 26 0 12 Feb 2021
A New Framework for Variance-Reduced Hamiltonian Monte Carlo Zhengmian Hu Feihu Huang Heng-Chiao Huang 34 0 0 09 Feb 2021
Simulated annealing from continuum to discretization: a convergence analysis via the Eyring--Kramers law Wenpin Tang X. Zhou 65 10 0 03 Feb 2021
The shifted ODE method for underdamped Langevin MCMC James Foster Terry Lyons Harald Oberhauser 93 16 0 10 Jan 2021
Particle Dual Averaging: Optimization of Mean Field Neural Networks with Global Convergence Rate Analysis Atsushi Nitanda Denny Wu Taiji Suzuki 86 29 0 31 Dec 2020
Variational Transport: A Convergent Particle-BasedAlgorithm for Distributional Optimization Zhuoran Yang Yufeng Zhang Yongxin Chen Zhaoran Wang OT 91 5 0 21 Dec 2020
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 66 35 0 06 Nov 2020
Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC Arun Ganesh Kunal Talwar FedML 84 41 0 27 Oct 2020
Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev Tianlin Li Qi Lei Ioannis Panageas 65 20 0 11 Oct 2020
On the cost of Bayesian posterior mean strategy for log-concave models S. Gadat Fabien Panloup Clément Pellegrini 57 7 0 08 Oct 2020
A Decentralized Approach to Bayesian Learning Anjaly Parayil H. Bai Jemin George Prudhvi K. Gurram 50 2 0 14 Jul 2020
High-dimensional MCMC with a standard splitting scheme for the underdamped Langevin diffusion Pierre Monmarché 98 47 0 10 Jul 2020
Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets Avetik G. Karagulyan A. Dalalyan 50 8 0 24 Jun 2020
Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm Adil Salim Peter Richtárik 78 40 0 16 Jun 2020
Hessian-Free High-Resolution Nesterov Acceleration for Sampling Ruilin Li H. Zha Molei Tao 72 8 0 16 Jun 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence Sinho Chewi Thibaut Le Gouic Chen Lu Tyler Maunu Philippe Rigollet 100 70 0 03 Jun 2020
CoolMomentum: A Method for Stochastic Optimization by Langevin Dynamics with Simulated Annealing O. Borysenko M. Byshkin ODL 58 14 0 29 May 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness Murat A. Erdogdu Rasa Hosseinzadeh 88 77 0 27 May 2020
Exponential ergodicity of mirror-Langevin diffusions Sinho Chewi Thibaut Le Gouic Chen Lu Tyler Maunu Philippe Rigollet Austin J. Stromme 82 51 0 19 May 2020
Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function Lingkai Kong Molei Tao 57 23 0 14 Feb 2020
Stochastic Approximate Gradient Descent via the Langevin Algorithm Yixuan Qiu Tianlin Li 52 4 0 13 Feb 2020
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization Ömer Deniz Akyildiz Sotirios Sabanis 97 17 0 13 Feb 2020
Variational Optimization on Lie Groups, with Examples of Leading (Generalized) Eigenvalue Problems Molei Tao T. Ohsawa DRL 93 17 0 27 Jan 2020
Information Newton's flow: second-order optimization method in probability space Yifei Wang Wuchen Li 109 31 0 13 Jan 2020
Estimating Normalizing Constants for Log-Concave Distributions: Algorithms and Lower Bounds Rong Ge Holden Lee Jianfeng Lu 78 22 0 08 Nov 2019
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry Andre Wibisono 140 49 0 04 Nov 2019
The Randomized Midpoint Method for Log-Concave Sampling Ruoqi Shen Y. Lee 125 118 0 12 Sep 2019
Accelerated Information Gradient flow Yifei Wang Wuchen Li 86 57 0 04 Sep 2019
High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm Wenlong Mou Yian Ma Martin J. Wainwright Peter L. Bartlett Michael I. Jordan DiffM 81 85 0 28 Aug 2019
Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimation Valentin De Bortoli Alain Durmus Marcelo Pereyra A. F. Vidal 93 33 0 28 Jun 2019
Bounding the error of discretized Langevin algorithms for non-strongly log-concave targets A. Dalalyan Avetik G. Karagulyan L. Riou-Durand 111 39 0 20 Jun 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond Xuechen Li Denny Wu Lester W. Mackey Murat A. Erdogdu 96 71 0 19 Jun 2019
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates Adil Salim D. Kovalev Peter Richtárik 81 26 0 28 May 2019