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The dominant term in PAC-Bayes bounds is often the Kullback--Leibler divergence between the posterior and prior.
“A Primer on PAC-Bayesian Learning”
Benjamin Guedj · 1901
Earlier work this paper cites.
“PAC-Bayes with Backprop”, 2019
Omar Rivasplata, Vikram Tankasali and Csaba Szepesvari · 1908
Earlier work this paper cites.
“A framework for structural risk minimisation”
John Shawe-Taylor, Peter Bartlett, Robert Williamson and Martin Anthony · 1996
Earlier work this paper cites.
“A PAC analysis of a Bayesian estimator”
John Shawe-Taylor and Robert Williamson · 1997
Earlier work this paper cites.
“MNIST handwritten digit database”, 1998
Yann LeCun, Corinna Cortes and Christopher.. Burges · 1998
Earlier work this paper cites.
“PAC-Bayesian Model Averaging”
David. McAllester · 1999
Earlier work this paper cites.
“Some PAC-Bayesian Theorems”
David. McAllester · 1999
Earlier work this paper cites.
“Bounds for Averaging Classifiers”, 2001
John Langford and Matthias Seeger · 2001
Earlier work this paper cites.
“Quantitatively tight sample complexity bounds”, 2002
John Langford · 2002
Earlier work this paper cites.
“Microchoice bounds and self bounding learning algorithms”
John Langford and Avrim Blum · 2003
Earlier work this paper cites.
“A note on the PAC-Bayesian theorem”, 2004
Andreas Maurer · 2004
Cited alongside, same era.
“Tighter PAC-Bayes bounds”
Amiran Ambroladze, Emilio Parrado-Hernández and John Shawe-Taylor · 2007
Cited alongside, same era.
“PAC-Bayesian supervised classification: the thermodynamics of statistical learning” 56
Olivier Catoni · 2007
Cited alongside, same era.
“Learning multiple layers of features from tiny images”, 2009
Alex Krizhevsky · 2009
Cited alongside, same era.
“Distribution-dependent PAC-Bayes priors”
Guy Lever, François Laviolette and John Shawe-Taylor · 2010
Cited alongside, same era.
“PAC-Bayes bounds with data dependent priors”
Emilio Parrado-Hernández, Amiran Ambroladze, John Shawe-Taylor and Shiliang Sun · 2012
Cited alongside, same era.
“Differential privacy and generalization: Sharper bounds with applications”
Luca Oneto, Sandro Ridella and Davide Anguita · 2017
Later among the works it cites.
“Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms”, 2017
Han Xiao, Kashif Rasul and Roland Vollgraf · 2017
Later among the works it cites.
“Data-dependent PAC-Bayes priors via differential privacy”
Gintare Dziugaite and Daniel. Roy · 2018
Later among the works it cites.
“A PAC-Bayesian approach to spectrally-normalized margin bounds for neural networks”
Behnam Neyshabur, Srinadh Bhojanapalli, David McAllester and Nathan Srebro · 2018
Later among the works it cites.
“PAC-Bayes bounds for stable algorithms with instance-dependent priors”
Omar Rivasplata et al · 2018
Later among the works it cites.
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“A PAC-Bayesian Tutorial with A Dropout Bound”, 2013
David. McAllester · 2013
Cited alongside, same era.
“Deep residual learning for image recognition”
Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun · 2016
Cited alongside, same era.
“PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis”
Luca Oneto, Davide Anguita and Sandro Ridella · 2016
Cited alongside, same era.
Gintare Dziugaite and Daniel. Roy · 2017
Cited alongside, same era.
“Uniform convergence may be unable to explain generalization in deep learning”
Vaishnavh Nagarajan and J. Kolter · 2019
Later among the works it cites.
“Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience” See also https://openreview.net/forum?id=Hygn2o0qKX , 2019
Vaishnavh Nagarajan and Zico Kolter · 2019
Later among the works it cites.
“Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates”
Jeffrey Negrea et al · 2019
Later among the works it cites.
“Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach”
Wenda Zhou et al · 2019
Later among the works it cites.