Review
Sep 2026
Optimization with Region-Reduced ReLU Neural Networks
This work proposes a novel \emph{region-reduced} model compression approach that combines the stabilization of unstable neurons and the merging of redundant neurons to reduce the number of linear regions while maintaining predictive accuracy through error compensation.
Christoph Plate, C. Ganzer, Mirko Hahn et al.
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