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20182020
most citedA New Compensatory Genetic Algorithm-Based Method for Effective Compressed Multi-function Convolutional Neural Network Model Selection with Multi-Objective Optimization

5 citations · 9 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG20203 cited

Pairwise Neural Networks (PairNets) with Low Memory for Fast On-Device Applications

Luna M. Zhang

A traditional artificial neural network (ANN) is normally trained slowly by a gradient descent algorithm, such as the backpropagation algorithm, since a large number of hyperparame…

cs.LG20201 cited

PairNets: Novel Fast Shallow Artificial Neural Networks on Partitioned Subspaces

Luna M. Zhang

Traditionally, an artificial neural network (ANN) is trained slowly by a gradient descent algorithm such as the backpropagation algorithm since a large number of hyperparameters of…

cs.NE20195 cited

A New Compensatory Genetic Algorithm-Based Method for Effective Compressed Multi-function Convolutional Neural Network Model Selection with Multi-Objective Optimization

Luna M. Zhang

In recent years, there have been many popular Convolutional Neural Networks (CNNs), such as Google's Inception-V4, that have performed very well for various image classification pr…

cs.CV2018

Effective, Fast, and Memory-Efficient Compressed Multi-function Convolutional Neural Networks for More Accurate Medical Image Classification

Luna M. Zhang

Convolutional Neural Networks (CNNs) usually use the same activation function, such as RELU, for all convolutional layers. There are performance limitations of just using RELU. In…

cs.CV2018

Multi-function Convolutional Neural Networks for Improving Image Classification Performance

Luna M. Zhang

Traditional Convolutional Neural Networks (CNNs) typically use the same activation function (usually ReLU) for all neurons with non-linear mapping operations. For example, the deep…