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"

21 / 21 papers shown

Title
Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes I. Harel Yonathan Wolanowsky Gal Vardi Nathan Srebro Daniel Soudry AI4CE 34 0 0 25 May 2025
ORIGEN: Zero-Shot 3D Orientation Grounding in Text-to-Image Generation Yunhong Min Daehyeon Choi Kyeongmin Yeo Jihyun Lee Minhyuk Sung 74 0 0 28 Mar 2025
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 125 3 0 28 Jan 2025
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 336 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 77 3 0 26 Apr 2024
Information-Theoretic Generalization Bounds for Deep Neural Networks Haiyun He Christina Lee Yu 75 5 0 04 Apr 2024
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation Ö. Deniz Akyildiz F. R. Crucinio Mark Girolami Tim Johnston Sotirios Sabanis 57 13 0 23 Mar 2023
Generalisation under gradient descent via deterministic PAC-Bayes Eugenio Clerico Tyler Farghly George Deligiannidis Benjamin Guedj Arnaud Doucet 50 4 0 06 Sep 2022
Uncertainty in Gradient Boosting via Ensembles Aleksei Ustimenko Liudmila Prokhorenkova A. Malinin UQCV 45 95 0 18 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 68 50 0 14 Jun 2020
The Implicit Regularization of Stochastic Gradient Flow for Least Squares Alnur Ali Yan Sun Robert Tibshirani 51 76 0 17 Mar 2020
An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng Xiao Zhang F. Liang Guang Lin BDL 91 44 0 23 Oct 2019
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys Pratik Chaudhari A. Choromańska Stefano Soatto Yann LeCun Carlo Baldassi C. Borgs J. Chayes Levent Sagun R. Zecchina ODL 82 769 0 06 Nov 2016
Train faster, generalize better: Stability of stochastic gradient descent Moritz Hardt Benjamin Recht Y. Singer 88 1,234 0 03 Sep 2015
Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 50 410 0 17 Jul 2015
Sampling from a log-concave distribution with Projected Langevin Monte Carlo Sébastien Bubeck Ronen Eldan Joseph Lehec 46 137 0 09 Jul 2015
On Graduated Optimization for Stochastic Non-Convex Problems Elad Hazan Kfir Y. Levy Shai Shalev-Shwartz 41 115 0 12 Mar 2015
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition Rong Ge Furong Huang Chi Jin Yang Yuan 112 1,056 0 06 Mar 2015
Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions A. Belloni Tengyuan Liang Hariharan Narayanan Alexander Rakhlin 79 77 0 28 Jan 2015
Theoretical guarantees for approximate sampling from smooth and log-concave densities A. Dalalyan 57 514 0 23 Dec 2014
Sparse Regression Learning by Aggregation and Langevin Monte-Carlo A. Dalalyan Alexandre B. Tsybakov 150 179 0 06 Mar 2009