2022
DOI: 10.48550/arxiv.2201.00723
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A Mixed-Integer Programming Approach to Training Dense Neural Networks

Abstract: Artificial Neural Networks (ANNs) are prevalent machine learning models that have been applied across various real world classification tasks. ANNs require a large amount of data to have strong out of sample performance, and many algorithms for training ANN parameters are based on stochastic gradient descent (SGD). However, the SGD ANNs that tend to perform best on prediction tasks are trained in an end to end manner that requires a large number of model parameters and random initialization. This means trainin… Show more

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