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07/19/2022
Neural Greedy Pursuit for Feature Selection
We propose a greedy algorithm to select N important features among P inp...
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10/06/2021
Use of Deterministic Transforms to Design Weight Matrices of a Neural Network
Self size-estimating feedforward network (SSFN) is a feedforward multila...
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11/18/2020
Statistical model-based evaluation of neural networks
Using a statistical model-based data generation, we develop an experimen...
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10/22/2020
A ReLU Dense Layer to Improve the Performance of Neural Networks
We propose ReDense as a simple and low complexity way to improve the per...
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09/29/2020
A Low Complexity Decentralized Neural Net with Centralized Equivalence using Layer-wise Learning
We design a low complexity decentralized learning algorithm to train a r...
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05/07/2020
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University
We provide a predictive analysis of the spread of COVID-19, also known a...
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04/10/2020
Asynchronous Decentralized Learning of a Neural Network
In this work, we exploit an asynchronous computing framework namely ARoc...
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03/29/2020
High-dimensional Neural Feature using Rectified Linear Unit and Random Matrix Instance
We design a ReLU-based multilayer neural network to generate a rich high...
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05/17/2019
SSFN: Self Size-estimating Feed-forward Network and Low Complexity Design
We design a self size-estimating feed-forward network (SSFN) using a joi...
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03/12/2018
R3Net: Random Weights, Rectifier Linear Units and Robustness for Artificial Neural Network
We consider a neural network architecture with randomized features, a si...
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10/23/2017
