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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"

47 / 97 papers shown

Title
State-Dependent Temperature Control for Langevin Diffusions Xuefeng Gao Z. Xu X. Zhou 167 29 0 15 Nov 2020
Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate Jingfeng Wu Difan Zou Vladimir Braverman Quanquan Gu 122 18 0 04 Nov 2020
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions Wei Deng Guang Lin F. Liang BDL 112 29 0 19 Oct 2020
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling Difan Zou Pan Xu Quanquan Gu 178 37 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 115 9 0 02 Oct 2020
Adversarially Robust Learning via Entropic Regularization Gauri Jagatap Ameya Joshi A. B. Chowdhury S. Garg Chinmay Hegde OOD 159 12 0 27 Aug 2020
Efficient hyperparameter optimization by way of PAC-Bayes bound minimization John J. Cherian Andrew G. Taube R. McGibbon Panagiotis Angelikopoulos Guy Blanc M. Snarski D. D. Richman J. L. Klepeis D. Shaw 67 5 0 14 Aug 2020
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC Wei Deng Qi Feng Liyao (Mars) Gao F. Liang Guang Lin BDL 121 49 0 12 Aug 2020
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum Zeke Xie Xinrui Wang Huishuai Zhang Issei Sato Masashi Sugiyama ODL 200 52 0 29 Jun 2020
Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms A. Lovas Iosif Lytras Miklós Rásonyi Sotirios Sabanis 92 27 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 154 53 0 14 Jun 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness Murat A. Erdogdu Rasa Hosseinzadeh 114 81 0 27 May 2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations Huan Zhang Hongge Chen Chaowei Xiao Yue Liu Mingyan D. Liu Duane S. Boning Cho-Jui Hsieh AAML 217 300 0 19 Mar 2020
Dimension-free convergence rates for gradient Langevin dynamics in RKHS Boris Muzellec Kanji Sato Mathurin Massias Taiji Suzuki 177 12 0 29 Feb 2020
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise Umut Simsekli Lingjiong Zhu Yee Whye Teh Mert Gurbuzbalaban 130 52 0 13 Feb 2020
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization Ömer Deniz Akyildiz Sotirios Sabanis 162 18 0 13 Feb 2020
Replica Exchange for Non-Convex Optimization Jing-rong Dong Xin T. Tong 160 21 0 23 Jan 2020
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks Umut Simsekli Mert Gurbuzbalaban T. H. Nguyen G. Richard Levent Sagun 136 60 0 29 Nov 2019
Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo Bao Wang Difan Zou Quanquan Gu Stanley Osher BDL 76 9 0 02 Nov 2019
An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng Xiao Zhang F. Liang Guang Lin BDL 148 45 0 23 Oct 2019
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization Ying Zhang Ömer Deniz Akyildiz Theodoros Damoulas Sotirios Sabanis 175 51 0 04 Oct 2019
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise T. H. Nguyen Umut Simsekli Mert Gurbuzbalaban G. Richard 95 69 0 21 Jun 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond Xuechen Li Denny Wu Lester W. Mackey Murat A. Erdogdu 149 73 0 19 Jun 2019
Langevin Monte Carlo without smoothness Niladri S. Chatterji Jelena Diakonikolas Michael I. Jordan Peter L. Bartlett BDL 122 45 0 30 May 2019
On stochastic gradient Langevin dynamics with dependent data streams: the fully non-convex case N. H. Chau '. Moulines Miklós Rásonyi Sotirios Sabanis Ying Zhang 143 42 0 30 May 2019
On Stationary-Point Hitting Time and Ergodicity of Stochastic Gradient Langevin Dynamics Xi Chen S. Du Xin T. Tong 110 33 0 30 Apr 2019
Convergence rates for the stochastic gradient descent method for non-convex objective functions Benjamin J. Fehrman Benjamin Gess Arnulf Jentzen 133 104 0 02 Apr 2019
Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning Huy N. Chau M. Rásonyi 79 11 0 25 Mar 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 151 286 0 11 Feb 2019
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning Jian Li Xuanyuan Luo Mingda Qiao 141 92 0 02 Feb 2019
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization T. H. Nguyen Umut Simsekli G. Richard 104 29 0 22 Jan 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks Umut Simsekli Levent Sagun Mert Gurbuzbalaban 231 268 0 18 Jan 2019
Breaking Reversibility Accelerates Langevin Dynamics for Global Non-Convex Optimization Xuefeng Gao Mert Gurbuzbalaban Lingjiong Zhu 112 33 0 19 Dec 2018
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 108 42 0 06 Dec 2018
Global Non-convex Optimization with Discretized Diffusions Murat A. Erdogdu Lester W. Mackey Ohad Shamir 130 106 0 29 Oct 2018
Stochastic Gradient MCMC for State Space Models Christopher Aicher Yian Ma N. Foti E. Fox 133 23 0 22 Oct 2018
Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and Momentum-Based Acceleration Xuefeng Gao Mert Gurbuzbalaban Lingjiong Zhu 144 63 0 12 Sep 2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang Ruiyi Zhang Lawrence Carin Changyou Chen 182 46 0 05 Sep 2018
On sampling from a log-concave density using kinetic Langevin diffusions A. Dalalyan L. Riou-Durand 195 163 0 24 Jul 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 143 151 0 20 Jun 2018
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization Umut Simsekli Çağatay Yıldız T. H. Nguyen G. Richard A. Cemgil 89 22 0 07 Jun 2018
Adaptive Stochastic Gradient Langevin Dynamics: Taming Convergence and Saddle Point Escape Time Hejian Sang Jia-Wei Liu ODL 126 1 0 23 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 116 171 0 04 May 2018
Analysis of Langevin Monte Carlo via convex optimization Alain Durmus Szymon Majewski B. Miasojedow 151 228 0 26 Feb 2018
Stochastic Variance-Reduced Cubic Regularized Newton Method Dongruo Zhou Pan Xu Quanquan Gu ODL 93 45 0 13 Feb 2018
Stochastic Variance-Reduced Hamilton Monte Carlo Methods Difan Zou Pan Xu Quanquan Gu BDL 90 32 0 13 Feb 2018
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient A. Dalalyan Avetik G. Karagulyan 237 303 0 29 Sep 2017