Neural network approximation and estimation of classifiers with
classification boundary in a Barron class

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Neural network approximation and estimation of classifiers with classification boundary in a Barron class

18 November 2020

F. Voigtlaender

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Papers citing "Neural network approximation and estimation of classifiers with classification boundary in a Barron class"

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Title
High-dimensional classification problems with Barron regular boundaries under margin conditions Jonathan García Philipp Petersen 112 1 0 10 Dec 2024
A priori estimates for classification problems using neural networks E. Weinan Stephan Wojtowytsch 40 8 0 28 Sep 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 74 134 0 22 Sep 2020
On the Banach spaces associated with multi-layer ReLU networks: Function representation, approximation theory and gradient descent dynamics E. Weinan Stephan Wojtowytsch MLT 44 53 0 30 Jul 2020
Rectified deep neural networks overcome the curse of dimensionality for nonsmooth value functions in zero-sum games of nonlinear stiff systems C. Reisinger Yufei Zhang 40 70 0 15 Mar 2019
Optimal Approximation with Sparsely Connected Deep Neural Networks Helmut Bölcskei Philipp Grohs Gitta Kutyniok P. Petersen 197 255 0 04 May 2017
Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks Peter L. Bartlett Nick Harvey Christopher Liaw Abbas Mehrabian 208 432 0 08 Mar 2017
On the ability of neural nets to express distributions Holden Lee Rong Ge Tengyu Ma Andrej Risteski Sanjeev Arora BDL 64 84 0 22 Feb 2017
Why and When Can Deep -- but Not Shallow -- Networks Avoid the Curse of Dimensionality: a Review T. Poggio H. Mhaskar Lorenzo Rosasco Brando Miranda Q. Liao 97 576 0 02 Nov 2016
Provable approximation properties for deep neural networks Uri Shaham A. Cloninger Ronald R. Coifman 172 231 0 24 Sep 2015