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06/16/2023
Representation and decomposition of functions in DAG-DNNs and structural network pruning
The conclusions provided by deep neural networks (DNNs) must be carefull...
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07/12/2022
Deriving RIP sensing matrices for sparsifying dictionaries
Compressive sensing involves the inversion of a mapping SD ∈ℝ^m × n, whe...
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06/13/2022
Analysis of function approximation and stability of general DNNs in directed acyclic graphs using un-rectifying analysis
A general lack of understanding pertaining to deep feedforward neural ne...
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01/18/2021
Learning DNN networks using un-rectifying ReLU with compressed sensing application
The un-rectifying technique expresses a non-linear point-wise activation...
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03/29/2019
Deep Representation with ReLU Neural Networks
We consider deep feedforward neural networks with rectified linear units...
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12/02/2018
Link Delay Estimation Using Sparse Recovery for Dynamic Network Tomography
When the scale of communication networks has been growing rapidly in the...
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01/06/2018
Frame-based Sparse Analysis and Synthesis Signal Representations and Parseval K-SVD
Frames are the foundation of the linear operators used in the decomposit...
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12/14/2015
