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New ReLU network representations for MAX functions developed

By PulseAugur Editorial · [1 sources] ·

Researchers have developed new two-hidden-layer ReLU neural network representations for MAX functions, specifically for MAX_5, MAX_6, MAX_7, and MAX_8. These findings contribute to the ongoing effort to characterize the exact number of hidden layers needed to represent continuous piecewise linear functions. The new representations were discovered through a computer-assisted search and differ from previously obtained results. AI

RANK_REASON The cluster contains an academic paper detailing new theoretical findings in machine learning. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv stat.ML →

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New ReLU network representations for MAX functions developed

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The cluster contains an academic paper detailing new theoretical findings in machine learning. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Zhimao Wang, Amitabh Basu ·

    Representing MAX functions using two-hidden-layer ReLU networks

    arXiv:2608.25221v1 Announce Type: cross Abstract: We study exact representations of $\mathrm{MAX}_N(x)=\max{x_1,\ldots,x_N}$ using two-hidden-layer ReLU neural networks. This problem has been studied in recent years in an attempt to characterize the exact number of hidden layers …

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