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Shallower ReLU Network Representations via Exact Linear Algebra

Rueß, Kilian et al.
arXiv (All) · Papers
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combinatoricsmachine-learningneural-and-evolutionary-computing
We study the depth required by ReLU networks to exactly represent piecewise linear functions, focusing specifically on the maximum function. This problem has recently received significant attention in both the ML and TCS literature. We prove that $\max_n(x)=\max\{x_1,\ldots,x_n\}$ is exactly represe
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