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Updated: Feb 25, 2026

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
Published on: September 25, 2021
A new type of neurons for machine learning
Fenglei Fan1, Wenxiang Cong1, Ge Wang1
1Biomedical Imaging Center, BME/CBIS, Rensselaer Polytechnic Institute, Troy, New York, USA.
Abstract:
In machine learning, an artificial neural network is the mainstream approach. Such a network consists of many neurons. These neurons are of the same type characterized by the 2 features: (1) an inner product of an input vector and a matching weighting vector of trainable parameters and (2) a nonlinear excitation function. Here, we investigate the possibility of replacing the inner product with a quadratic function of the input vector, thereby upgrading the first-order neuron to the second-order neuron, empowering individual neurons and facilitating the optimization of neural networks. Also, numerical examples are provided to illustrate the feasibility and merits of the second-order neurons. Finally, further topics are discussed.
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