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07/28/2023
Weighted variation spaces and approximation by shallow ReLU networks
We investigate the approximation of functions f on a bounded domain Ω⊂ℝ^...
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05/25/2023
Vector-Valued Variation Spaces and Width Bounds for DNNs: Insights on Weight Decay Regularization
Deep neural networks (DNNs) trained to minimize a loss term plus the sum...
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01/23/2023
Deep Learning Meets Sparse Regularization: A Signal Processing Perspective
Deep learning has been wildly successful in practice and most state-of-t...
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09/18/2021
Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks
We study the problem of estimating an unknown function from noisy data u...
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05/07/2021
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory
We develop a variational framework to understand the properties of funct...
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06/10/2020
Neural Networks, Ridge Splines, and TV Regularization in the Radon Domain
We develop a variational framework to understand the properties of the f...
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10/05/2019