A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics

18 February 2017

Papers citing "A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics"

23 / 23 papers shown

Title
Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random Gautam Chandrasekaran Vasilis Kontonis Konstantinos Stavropoulos Kevin Tian 109 1 0 20 Jan 2025
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling Matthew Burns Qingyuan Hou Michael Huang 345 1 0 08 Oct 2024
Quantum Langevin Dynamics for Optimization Zherui Chen Yuchen Lu Hao Wang Yizhou Liu Tongyang Li AI4CE 66 11 0 27 Nov 2023
An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng Xiao Zhang F. Liang Guang Lin BDL 91 44 0 23 Oct 2019
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 64 518 0 13 Feb 2017
A Comprehensive Study of Deep Bidirectional LSTM RNNs for Acoustic Modeling in Speech Recognition Albert Zeyer P. Doetsch P. Voigtlaender Ralf Schluter Hermann Ney 46 169 0 22 Jun 2016
Efficient approaches for escaping higher order saddle points in non-convex optimization Anima Anandkumar Rong Ge 25 143 0 18 Feb 2016
Gradient Descent Converges to Minimizers Jason D. Lee Max Simchowitz Michael I. Jordan Benjamin Recht 55 211 0 16 Feb 2016
Guarantees in Wasserstein Distance for the Langevin Monte Carlo Algorithm Thomas Bonis 19 2 0 08 Feb 2016
Neural GPUs Learn Algorithms Lukasz Kaiser Ilya Sutskever 69 369 0 25 Nov 2015
Adding Gradient Noise Improves Learning for Very Deep Networks Arvind Neelakantan Luke Vilnis Quoc V. Le Ilya Sutskever Lukasz Kaiser Karol Kurach James Martens AI4CE ODL 44 544 0 21 Nov 2015
Neural Random-Access Machines Karol Kurach Marcin Andrychowicz Ilya Sutskever OOD BDL 60 156 0 19 Nov 2015
Neural Programmer: Inducing Latent Programs with Gradient Descent Arvind Neelakantan Quoc V. Le Ilya Sutskever ODL 59 263 0 16 Nov 2015
On the Quality of the Initial Basin in Overspecified Neural Networks Itay Safran Ohad Shamir 56 127 0 13 Nov 2015
Efficient Learning of Linear Separators under Bounded Noise Pranjal Awasthi Maria-Florina Balcan Nika Haghtalab Ruth Urner 36 94 0 12 Mar 2015
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition Rong Ge Furong Huang Chi Jin Yang Yuan 125 1,056 0 06 Mar 2015
Theoretical guarantees for approximate sampling from smooth and log-concave densities A. Dalalyan 66 514 0 23 Dec 2014
Consistency and fluctuations for stochastic gradient Langevin dynamics Yee Whye Teh Alexandre Hoang Thiery Sebastian J. Vollmer 49 231 0 01 Sep 2014
Optimal rates for zero-order convex optimization: the power of two function evaluations John C. Duchi Michael I. Jordan Martin J. Wainwright Andre Wibisono 59 480 0 07 Dec 2013
Optimal computational and statistical rates of convergence for sparse nonconvex learning problems Zhaoran Wang Han Liu Tong Zhang 85 175 0 20 Jun 2013
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima Po-Ling Loh Martin J. Wainwright 194 516 0 10 May 2013
Advances in Optimizing Recurrent Networks Yoshua Bengio Nicolas Boulanger-Lewandowski Razvan Pascanu ODL 72 522 0 04 Dec 2012
On the difficulty of training Recurrent Neural Networks Razvan Pascanu Tomas Mikolov Yoshua Bengio ODL 134 5,318 0 21 Nov 2012