Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using
Total Path Variation

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Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation

2 February 2019

Andrew R. Barron

Jason M. Klusowski

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Papers citing "Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation"

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Title
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning Arthur Jacot Seok Hoan Choi Yuxiao Wen AI4CE 143 2 0 08 Jul 2024
Approximation bounds for norm constrained neural networks with applications to regression and GANs Yuling Jiao Yang Wang Yunfei Yang 85 20 0 24 Jan 2022
Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning Alberto Badías A. Banerjee 74 3 0 02 Jul 2021
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory Rahul Parhi Robert D. Nowak MLT 128 71 0 07 May 2021
Generalization bounds for deep learning Guillermo Valle Pérez A. Louis BDL 82 45 0 07 Dec 2020
Layer Sparsity in Neural Networks Mohamed Hebiri Johannes Lederer 92 10 0 28 Jun 2020
Banach Space Representer Theorems for Neural Networks and Ridge Splines Rahul Parhi Robert D. Nowak 33 7 0 10 Jun 2020
Statistical Guarantees for Regularized Neural Networks Mahsa Taheri Fang Xie Johannes Lederer 113 39 0 30 May 2020
Ensembled sparse-input hierarchical networks for high-dimensional datasets Jean Feng N. Simon 26 4 0 11 May 2020
Significance Tests for Neural Networks Enguerrand Horel K. Giesecke 57 56 0 16 Feb 2019