Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization

20 July 2017

Quanquan Gu

Papers citing "Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization"

34 / 34 papers shown

Title
Langevin Multiplicative Weights Update with Applications in Polynomial Portfolio Management Yi-Hu Feng Xiao Wang Tian Xie 52 0 0 26 Feb 2025
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 80 3 0 28 Jan 2025
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 111 1 0 08 Oct 2024
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data YongKyung Oh Dongyoung Lim Sungil Kim AI4TS 35 11 0 22 Feb 2024
The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank Amitay Bar Rotem Mulayoff T. Michaeli Ronen Talmon 54 0 0 21 Feb 2024
Generalization Bounds for Label Noise Stochastic Gradient Descent Jung Eun Huh Patrick Rebeschini 13 1 0 01 Nov 2023
High-Rate Phase Association with Travel Time Neural Fields Chengzhi Shi Maarten V. de Hoop Ivan Dokmanić 19 1 0 14 Jul 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 20 20 0 29 May 2023
Non-asymptotic analysis of Langevin-type Monte Carlo algorithms Shogo H. Nakakita 14 0 0 22 Mar 2023
Non-convex sampling for a mixture of locally smooth potentials D. Nguyen 33 0 0 31 Jan 2023
Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions Marelys Crespo Navas S. Gadat X. Gendre 19 0 0 08 Jan 2023
A Dynamical System View of Langevin-Based Non-Convex Sampling Mohammad Reza Karimi Ya-Ping Hsieh Andreas Krause 29 4 0 25 Oct 2022
Fisher information lower bounds for sampling Sinho Chewi P. Gerber Holden Lee Chen Lu 40 15 0 05 Oct 2022
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems Giannis Daras Y. Dagan A. Dimakis C. Daskalakis BDL 26 15 0 18 Jun 2022
Uniform Generalization Bound on Time and Inverse Temperature for Gradient Descent Algorithm and its Application to Analysis of Simulated Annealing Keisuke Suzuki AI4CE 17 0 0 25 May 2022
An Empirical Study of the Occurrence of Heavy-Tails in Training a ReLU Gate Sayar Karmakar Anirbit Mukherjee 16 0 0 26 Apr 2022
Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng Siqi Liang Botao Hao Guang Lin F. Liang BDL 21 10 0 20 Feb 2022
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo Krishnakumar Balasubramanian Sinho Chewi Murat A. Erdogdu Adil Salim Matthew Shunshi Zhang 35 60 0 10 Feb 2022
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 14 17 0 06 May 2021
Stochastic Gradient Langevin Dynamics with Variance Reduction Zhishen Huang Stephen Becker 13 7 0 12 Feb 2021
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions Wei Deng Guang Lin F. Liang BDL 34 27 0 19 Oct 2020
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction Wei Deng Qi Feng G. Karagiannis Guang Lin F. Liang 14 8 0 02 Oct 2020
Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms A. Lovas Iosif Lytras Miklós Rásonyi Sotirios Sabanis 15 25 0 25 Jun 2020
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 19 50 0 14 Jun 2020
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization Ömer Deniz Akyildiz Sotirios Sabanis 33 17 0 13 Feb 2020
Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning Huy N. Chau M. Rásonyi 17 10 0 25 Mar 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks Umut Simsekli Levent Sagun Mert Gurbuzbalaban 8 237 0 18 Jan 2019
On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case M. Barkhagen N. H. Chau '. Moulines Miklós Rásonyi S. Sabanis Ying Zhang 13 37 0 06 Dec 2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang Ruiyi Zhang Lawrence Carin Changyou Chen 10 46 0 05 Sep 2018
On sampling from a log-concave density using kinetic Langevin diffusions A. Dalalyan L. Riou-Durand 11 155 0 24 Jul 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 22 146 0 20 Jun 2018
Stochastic Variance-Reduced Hamilton Monte Carlo Methods Difan Zou Pan Xu Quanquan Gu BDL 19 31 0 13 Feb 2018
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 32 158 0 21 Oct 2016
MCMC using Hamiltonian dynamics Radford M. Neal 176 3,260 0 09 Jun 2012