Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis

13 February 2017

Papers citing "Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis"

50 / 114 papers shown

Title
Operator-Level Quantum Acceleration of Non-Logconcave Sampling Jiaqi Leng Zhiyan Ding Zherui Chen Lin Lin 62 0 0 08 May 2025
Langevin Multiplicative Weights Update with Applications in Polynomial Portfolio Management Yi-Hu Feng Tianlin Li Tian Xie 62 0 0 26 Feb 2025
Understanding the Generalization Error of Markov algorithms through Poissonization Benjamin Dupuis Maxime Haddouche George Deligiannidis Umut Simsekli 47 0 0 11 Feb 2025
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 93 3 0 28 Jan 2025
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 137 1 0 08 Oct 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets Benjamin Dupuis Paul Viallard George Deligiannidis Umut Simsekli 42 2 0 26 Apr 2024
Information-Theoretic Generalization Bounds for Deep Neural Networks Haiyun He Christina Lee Yu 35 4 0 04 Apr 2024
Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping Umut Simsekli Mert Gurbuzbalaban S. Yıldırım Lingjiong Zhu 38 2 0 04 Mar 2024
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data YongKyung Oh Dongyoung Lim Sungil Kim AI4TS 43 12 0 22 Feb 2024
The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank Amitay Bar Rotem Mulayoff T. Michaeli Ronen Talmon 64 0 0 21 Feb 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures Paul Viallard Rémi Emonet Amaury Habrard Emilie Morvant Valentina Zantedeschi 39 3 0 19 Feb 2024
Convex SGD: Generalization Without Early Stopping Julien Hendrickx A. Olshevsky MLT LRM 25 1 0 08 Jan 2024
Generalization Bounds for Label Noise Stochastic Gradient Descent Jung Eun Huh Patrick Rebeschini 13 1 0 01 Nov 2023
Gibbs-Based Information Criteria and the Over-Parameterized Regime Haobo Chen Yuheng Bu Greg Wornell 27 1 0 08 Jun 2023
Deep Stochastic Mechanics Elena Orlova Aleksei Ustimenko Ruoxi Jiang Peter Y. Lu Rebecca Willett DiffM 43 0 0 31 May 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 35 7 0 27 May 2023
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent Lingjiong Zhu Mert Gurbuzbalaban Anant Raj Umut Simsekli 31 6 0 20 May 2023
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models Anant Raj Umut Simsekli Alessandro Rudi DiffM 31 1 0 30 Mar 2023
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation Ö. Deniz Akyildiz F. R. Crucinio Mark Girolami Tim Johnston Sotirios Sabanis 32 11 0 23 Mar 2023
Non-asymptotic analysis of Langevin-type Monte Carlo algorithms Shogo H. Nakakita 19 0 0 22 Mar 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 31 6 0 08 Mar 2023
Revisiting the Noise Model of Stochastic Gradient Descent Barak Battash Ofir Lindenbaum 27 9 0 05 Mar 2023
Tighter Information-Theoretic Generalization Bounds from Supersamples Ziqiao Wang Yongyi Mao 32 17 0 05 Feb 2023
Non-convex sampling for a mixture of locally smooth potentials D. Nguyen 33 0 0 31 Jan 2023
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Mengdi Wang Furong Huang Dinesh Manocha 24 7 0 28 Jan 2023
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions Anant Raj Lingjiong Zhu Mert Gurbuzbalaban Umut Simsekli 28 15 0 27 Jan 2023
Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity -- the Strongly Convex Case Tim Johnston Iosif Lytras Sotirios Sabanis 38 8 0 19 Jan 2023
Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions Marelys Crespo Navas S. Gadat X. Gendre 26 0 0 08 Jan 2023
Fast Replica Exchange Stochastic Gradient Langevin Dynamics Guanxun Li Guang Lin Zecheng Zhang Quan Zhou 138 4 0 05 Jan 2023
Non-reversible Parallel Tempering for Deep Posterior Approximation Wei Deng Qian Zhang Qi Feng F. Liang Guang Lin 20 4 0 20 Nov 2022
Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States Ziqiao Wang Yongyi Mao 27 10 0 19 Nov 2022
Data-Adaptive Discriminative Feature Localization with Statistically Guaranteed Interpretation Ben Dai Xiaotong Shen Lingzhi Chen Chunlin Li Wei Pan FAtt 18 1 0 18 Nov 2022
A Dynamical System View of Langevin-Based Non-Convex Sampling Mohammad Reza Karimi Ya-Ping Hsieh Andreas Krause 40 4 0 25 Oct 2022
Global Convergence of SGD On Two Layer Neural Nets Pulkit Gopalani Anirbit Mukherjee 26 5 0 20 Oct 2022
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling Jason M. Altschuler Kunal Talwar 35 24 0 16 Oct 2022
Over-the-Air Split Machine Learning in Wireless MIMO Networks YuZhi Yang Zhaoyang Zhang Yuqing Tian Zhaohui Yang Chongwen Huang C. Zhong Kai‐Kit Wong 26 23 0 07 Oct 2022
Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms Hesameddin Mohammadi Meisam Razaviyayn Mihailo R. Jovanović 15 7 0 24 Sep 2022
Generalisation under gradient descent via deterministic PAC-Bayes Eugenio Clerico Tyler Farghly George Deligiannidis Benjamin Guedj Arnaud Doucet 31 4 0 06 Sep 2022
A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics Lei Li Yuliang Wang 39 11 0 19 Jul 2022
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems Giannis Daras Y. Dagan A. Dimakis C. Daskalakis BDL 31 15 0 18 Jun 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity A. F. Pour H. Ashtiani 30 3 0 14 Jun 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling Gerard Ben Arous Reza Gheissari Aukosh Jagannath 56 58 0 08 Jun 2022
Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms Aniket Das Dheeraj M. Nagaraj Anant Raj 54 6 0 08 Jun 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 26 19 0 01 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 30 0 0 25 May 2022
Weak Convergence of Approximate reflection coupling and its Application to Non-convex Optimization Keisuke Suzuki 25 5 0 24 May 2022
Decentralized Stochastic Optimization with Inherent Privacy Protection Yongqiang Wang H. Vincent Poor 24 37 0 08 May 2022
An Empirical Study of the Occurrence of Heavy-Tails in Training a ReLU Gate Sayar Karmakar Anirbit Mukherjee 18 0 0 26 Apr 2022
Sharper Utility Bounds for Differentially Private Models Yilin Kang Yong Liu Jian Li Weiping Wang FedML 29 3 0 22 Apr 2022
A Proximal Algorithm for Sampling Jiaming Liang Yongxin Chen 22 17 0 28 Feb 2022