4 citations · 7 across the 5 of their papers we have counts for
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math.NA2019★ 4 cited
Analysis of Deep Neural Networks with Quasi-optimal polynomial approximation rates
Joseph Daws, Clayton Webster
We show the existence of a deep neural network capable of approximating a wide class of high-dimensional approximations. The construction of the proposed neural network is based on…
eess.IV2019
A Weighted -Minimization Approach For Wavelet Reconstruction of Signals and Images
Joseph Daws, Armenak Petrosyan, Hoang Tran +1
In this effort, we propose a convex optimization approach based on weighted -regularization for reconstructing objects of interest, such as signals or images, that are spar…
cs.LG2019★ 3 cited
A Polynomial-Based Approach for Architectural Design and Learning with Deep Neural Networks
Joseph Daws, Clayton G. Webster
In this effort we propose a novel approach for reconstructing multivariate functions from training data, by identifying both a suitable network architecture and an initialization u…