Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory

5 September 2018

Jianyi Zhang

Papers citing "Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory"

32 / 32 papers shown

Title
Scalable Thompson Sampling via Optimal Transport Ruiyi Zhang Zheng Wen Changyou Chen Lawrence Carin OT 55 20 0 19 Feb 2019
Stochastic Zeroth-order Discretizations of Langevin Diffusions for Bayesian Inference Abhishek Roy Lingqing Shen Krishnakumar Balasubramanian Saeed Ghadimi 66 6 0 04 Feb 2019
Stein Variational Gradient Descent as Moment Matching Qiang Liu Dilin Wang 72 38 0 27 Oct 2018
Policy Optimization as Wasserstein Gradient Flows Ruiyi Zhang Changyou Chen Chunyuan Li Lawrence Carin 52 68 0 09 Aug 2018
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions Antoine Liutkus Umut Simsekli Szymon Majewski Alain Durmus Fabian-Robert Stöter DiffM 75 122 0 21 Jun 2018
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling Changyou Chen Ruiyi Zhang Wenlin Wang Bai Li Liqun Chen 49 89 0 29 May 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 47 166 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 60 87 0 15 Feb 2018
Learning Structural Weight Uncertainty for Sequential Decision-Making Ruiyi Zhang Chunyuan Li Changyou Chen Lawrence Carin BDL UQCV 60 26 0 30 Dec 2017
Riemannian Stein Variational Gradient Descent for Bayesian Inference Chang-rui Liu Jun Zhu 55 67 0 30 Nov 2017
Stein Variational Message Passing for Continuous Graphical Models Dilin Wang Zhe Zeng Qiang Liu 52 3 0 20 Nov 2017
Message Passing Stein Variational Gradient Descent Jingwei Zhuo Chang-rui Liu Jiaxin Shi Jun Zhu Ning Chen Bo Zhang 54 92 0 13 Nov 2017
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient A. Dalalyan Avetik G. Karagulyan 65 296 0 29 Sep 2017
Learning to Draw Samples with Amortized Stein Variational Gradient Descent Yihao Feng Dilin Wang Qiang Liu GAN BDL 58 81 0 20 Jul 2017
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization Pan Xu Jinghui Chen Difan Zou Quanquan Gu 68 205 0 20 Jul 2017
Stein Variational Gradient Descent as Gradient Flow Qiang Liu OT 67 275 0 25 Apr 2017
Stein Variational Policy Gradient Yang Liu Prajit Ramachandran Qiang Liu Jian-wei Peng 66 139 0 07 Apr 2017
Reinforcement Learning with Deep Energy-Based Policies Tuomas Haarnoja Haoran Tang Pieter Abbeel Sergey Levine 92 1,339 0 27 Feb 2017
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics Yuchen Zhang Percy Liang Moses Charikar 61 236 0 18 Feb 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 70 521 0 13 Feb 2017
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 66 161 0 21 Oct 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 65 1,091 0 16 Aug 2016
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos Max Welling BDL 60 257 0 15 Mar 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 79 325 0 23 Dec 2015
A Complete Recipe for Stochastic Gradient MCMC Yian Ma Tianqi Chen E. Fox BDL SyDa 60 486 0 15 Jun 2015
Stochastic Expectation Propagation Yingzhen Li Jose Miguel Hernandez-Lobato Richard Turner 122 115 0 12 Jun 2015
High-Dimensional Continuous Control Using Generalized Advantage Estimation John Schulman Philipp Moritz Sergey Levine Michael I. Jordan Pieter Abbeel OffRL 82 3,399 0 08 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 294 4,167 0 21 May 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 171 1,886 0 20 May 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 108 944 0 18 Feb 2015
Consistency and fluctuations for stochastic gradient Langevin dynamics Yee Whye Teh Alexandre Hoang Thiery Sebastian J. Vollmer 60 234 0 01 Sep 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 104 908 0 17 Feb 2014