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08/07/2023
Tractability of approximation by general shallow networks
In this paper, we present a sharper version of the results in the paper ...
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05/06/2023
Approximation by non-symmetric networks for cross-domain learning
For the past 30 years or so, machine learning has stimulated a great dea...
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03/02/2023
Encoding of data sets and algorithms
In many high-impact applications, it is important to ensure the quality ...
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02/13/2022
Local approximation of operators
Many applications, such as system identification, classification of time...
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10/04/2021
A manifold learning approach for gesture identification from micro-Doppler radar measurements
A recent paper (Neural Networks, 132 (2020), 253-268) introduces a strai...
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09/29/2021
Kernel distance measures for time series, random fields and other structured data
This paper introduces kdiff, a novel kernel-based measure for estimating...
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08/03/2020
Cautious Active Clustering
We consider a set of points sampled from an unknown probability measure ...
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08/01/2019
Deep Gaussian networks for function approximation on data defined manifolds
In much of the literature on function approximation by deep networks, th...
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02/17/2018
An analysis of training and generalization errors in shallow and deep networks
An open problem around deep networks is the apparent absence of over-fit...
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12/30/2017
