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The Computational Complexity of Counting Linear Regions in ReLU Neural Networks
combinatoricscomputational-complexitydiscrete-mathematicsmachine-learningneural-and-evolutionary-computing
An established measure of the expressive power of a given ReLU neural network is the number of linear regions into which it partitions the input space. There exist many different, non-equivalent definitions of what a linear region actually is. We systematically assess which papers use which definiti
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