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Global Non-convex Optimization with Discretized Diffusions

29 October 2018

Papers citing "Global Non-convex Optimization with Discretized Diffusions"

50 / 77 papers shown

Title
Restricted Spectral Gap Decomposition for Simulated Tempering Targeting Mixture Distributions Jhanvi Garg Krishna Balasubramanian Quan Zhou 123 0 0 21 May 2025
Online Inference for Quantiles by Constant Learning-Rate Stochastic Gradient Descent Ziyang Wei Jiaqi Li Likai Chen Wei Biao Wu 114 0 0 04 Mar 2025
On theoretical guarantees and a blessing of dimensionality for nonconvex sampling Martin Chak 104 2 0 12 Nov 2024
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers Ye He Alireza Mousavi-Hosseini Krishnakumar Balasubramanian Murat A. Erdogdu 81 2 0 27 May 2024
Parallelized Midpoint Randomization for Langevin Monte Carlo Lu Yu A. Dalalyan 75 7 0 22 Feb 2024
Stein Boltzmann Sampling: A Variational Approach for Global Optimization Gaetan Serré Argyris Kalogeratos Nicolas Vayatis OT 82 1 0 07 Feb 2024
Adam-like Algorithm with Smooth Clipping Attains Global Minima: Analysis Based on Ergodicity of Functional SDEs Keisuke Suzuki 53 0 0 29 Nov 2023
Generalization Bounds for Label Noise Stochastic Gradient Descent Jung Eun Huh Patrick Rebeschini 61 1 0 01 Nov 2023
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting Aleksei Ustimenko Aleksandr Beznosikov 82 1 0 09 Oct 2023
Langevin Quasi-Monte Carlo Sifan Liu BDL 53 4 0 22 Sep 2023
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements Emmanouil-Vasileios Vlatakis-Gkaragkounis Angeliki Giannou Yudong Chen Qiaomin Xie 52 4 0 28 Jun 2023
Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited Lu Yu Avetik G. Karagulyan A. Dalalyan 67 7 0 14 Jun 2023
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms Tim Tsz-Kit Lau Han Liu Thomas Pock 97 4 0 25 May 2023
Accelerating Convergence in Global Non-Convex Optimization with Reversible Diffusion Ryo Fujino 80 0 0 19 May 2023
Non-asymptotic analysis of Langevin-type Monte Carlo algorithms Shogo H. Nakakita 86 0 0 22 Mar 2023
Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincaré Inequality Alireza Mousavi-Hosseini Tyler Farghly Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 122 27 0 07 Mar 2023
Improved Discretization Analysis for Underdamped Langevin Monte Carlo Matthew Shunshi Zhang Sinho Chewi Mufan Li Krishnakumar Balasubramanian Murat A. Erdogdu 68 35 0 16 Feb 2023
Non-convex sampling for a mixture of locally smooth potentials D. Nguyen 82 0 0 31 Jan 2023
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions Anant Raj Lingjiong Zhu Mert Gurbuzbalaban Umut Simsekli 78 16 0 27 Jan 2023
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent Jiaxin Shi Lester W. Mackey 79 20 0 17 Nov 2022
Controlling Moments with Kernel Stein Discrepancies Heishiro Kanagawa Alessandro Barp Arthur Gretton Lester W. Mackey 82 9 0 10 Nov 2022
A Dynamical System View of Langevin-Based Non-Convex Sampling Mohammad Reza Karimi Ya-Ping Hsieh Andreas Krause 85 4 0 25 Oct 2022
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling Jason M. Altschuler Kunal Talwar 105 25 0 16 Oct 2022
$Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers$ Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$ -Covers Sejun Park Umut Simsekli Murat A. Erdogdu 105 9 0 19 Sep 2022
Generalisation under gradient descent via deterministic PAC-Bayes Eugenio Clerico Tyler Farghly George Deligiannidis Benjamin Guedj Arnaud Doucet 152 4 0 06 Sep 2022
Concentration analysis of multivariate elliptic diffusion processes Cathrine Aeckerle-Willems Claudia Strauch Lukas Trottner 96 1 0 07 Jun 2022
Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods Shunta Akiyama Taiji Suzuki 57 6 0 30 May 2022
Constrained Langevin Algorithms with L-mixing External Random Variables Yu Zheng Andrew G. Lamperski 83 6 0 27 May 2022
Uniform Generalization Bound on Time and Inverse Temperature for Gradient Descent Algorithm and its Application to Analysis of Simulated Annealing Keisuke Suzuki AI4CE 76 0 0 25 May 2022
Weak Convergence of Approximate reflection coupling and its Application to Non-convex Optimization Keisuke Suzuki 70 5 0 24 May 2022
Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng Siqi Liang Botao Hao Guang Lin F. Liang BDL 79 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 108 65 0 10 Feb 2022
On Uniform Boundedness Properties of SGD and its Momentum Variants Xiaoyu Wang M. Johansson 60 3 0 25 Jan 2022
Heavy-tailed Sampling via Transformed Unadjusted Langevin Algorithm Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 83 5 0 20 Jan 2022
Global convergence of optimized adaptive importance samplers Ömer Deniz Akyildiz 103 7 0 02 Jan 2022
Unadjusted Langevin algorithm for sampling a mixture of weakly smooth potentials D. Nguyen 58 5 0 17 Dec 2021
On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting Shunta Akiyama Taiji Suzuki MLT 116 13 0 11 Jun 2021
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks Dong-Young Lim Sotirios Sabanis 97 12 0 28 May 2021
Stein's Method Meets Computational Statistics: A Review of Some Recent Developments Andreas Anastasiou Alessandro Barp F. Briol B. Ebner Robert E. Gaunt ... Qiang Liu Lester W. Mackey Chris J. Oates Gesine Reinert Yvik Swan 101 35 0 07 May 2021
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 77 17 0 06 May 2021
Higher Order Generalization Error for First Order Discretization of Langevin Diffusion Mufan Li Maxime Gazeau 33 1 0 11 Feb 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
Projected Stochastic Gradient Langevin Algorithms for Constrained Sampling and Non-Convex Learning Andrew G. Lamperski 42 28 0 22 Dec 2020
Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods Taiji Suzuki Shunta Akiyama MLT 65 12 0 06 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
Riemannian Langevin Algorithm for Solving Semidefinite Programs Mufan Li Murat A. Erdogdu 118 29 0 21 Oct 2020
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions Wei Deng Guang Lin F. Liang BDL 78 28 0 19 Oct 2020
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling Difan Zou Pan Xu Quanquan Gu 108 36 0 19 Oct 2020
Robust, Accurate Stochastic Optimization for Variational Inference Akash Kumar Dhaka Alejandro Catalina Michael Riis Andersen Maans Magnusson Jonathan H. Huggins Aki Vehtari 71 34 0 01 Sep 2020
Blindness of score-based methods to isolated components and mixing proportions Wenliang K. Li Heishiro Kanagawa 94 34 0 23 Aug 2020