Distribution-Dependent Analysis of Gibbs-ERM Principle

5 February 2019

Papers citing "Distribution-Dependent Analysis of Gibbs-ERM Principle"

9 / 9 papers shown

Title
A PAC-Bayesian Link Between Generalisation and Flat Minima Maxime Haddouche Paul Viallard Umut Simsekli Benjamin Guedj 80 4 0 13 Feb 2024
Iterate averaging as regularization for stochastic gradient descent Gergely Neu Lorenzo Rosasco MoMe 71 61 0 22 Feb 2018
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability Belinda Tzen Tengyuan Liang Maxim Raginsky 40 32 0 18 Feb 2018
Information-theoretic analysis of generalization capability of learning algorithms Aolin Xu Maxim Raginsky 153 445 0 22 May 2017
Frequentist Consistency of Variational Bayes Yixin Wang David M. Blei BDL 101 208 0 09 May 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 70 521 0 13 Feb 2017
Fast Rates for Empirical Risk Minimization of Strict Saddle Problems Alon Gonen Shai Shalev-Shwartz 62 30 0 16 Jan 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 408 2,935 0 15 Sep 2016
A Variational Analysis of Stochastic Gradient Algorithms Stephan Mandt Matthew D. Hoffman David M. Blei 47 161 0 08 Feb 2016