Fetching the paper…
Reading the bibliography…
We study the sample complexity of learning ReLU neural networks from the point of view of generalization.
Probability in Banach Spaces: Isoperimetry and Processes
Michel Ledoux and Michel Talagrand · 1991
Earlier work this paper cites.
For valid generalization the size of the weights is more important than the size of the network
Peter Bartlett · 1996
Earlier work this paper cites.
Neural Network Learning: Theoretical Foundations
Martin Anthony and Peter L Bartlett · 1999
Earlier work this paper cites.
Rademacher and Gaussian complexities: Risk bounds and structural results
Peter L Bartlett and Shahar Mendelson · 2002
Earlier work this paper cites.
Concentration Inequalities: A Nonasymptotic Theory of Independence
Stéphane Boucheron, Gábor Lugosi, and Pascal Massart · 2013
Earlier work this paper cites.
Understanding Machine Learning: From Theory to Algorithms
Shai Shalev-Shwartz and Shai Ben-David · 2014
Cited alongside, same era.
Norm-based capacity control in neural networks
Behnam Neyshabur, Ryota Tomioka, and Nathan Srebro · 2015
Cited alongside, same era.
Spectrally-Normalized Margin Bounds for Neural Networks
Peter L Bartlett, Dylan J Foster, and Matus J Telgarsky · 2017
Cited alongside, same era.
Stronger generalization bounds for deep nets via a compression approach
Sanjeev Arora, Rong Ge, Behnam Neyshabur, and Yi Zhang · 2018
Cited alongside, same era.
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
Behnam Neyshabur, Srinadh Bhojanapalli, and Nathan Srebro · 2018
Cited alongside, same era.
Data-Dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation
Colin Wei and Tengyu Ma · 2019
Later among the works it cites.
On generalization bounds of a family of recurrent neural networks
Minshuo Chen, Xingguo Li, and Tuo Zhao · 2020
Later among the works it cites.
Generalization and representational limits of graph neural networks
Vikas Garg, Stefanie Jegelka, and Tommi Jaakkola · 2020
Later among the works it cites.
Size-Independent Sample Complexity of Neural Networks
Noah Golowich, Alexander Rakhlin, and Ohad Shamir · 2020
Later among the works it cites.
Generalization bounds for deep convolutional neural networks
Philip M Long and Hanie Sedghi · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…