#lipschitz

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2 curated events

papersTODAY 04:00 UTC

Paper Proposes Gershgorin-Based Method to Control Lipschitz Bounds in ResNets

A revised arXiv paper introduces an approach for deep residual networks that uses Gershgorin circle analysis to constrain Lipschitz constants. The work targets stability and robustness in ResNet architectures while preserving the gradient flow that makes deep residual models effective. The submission is a cross-listed replacement on arXiv's AI and machine learning categories.

resnets/lipschitz/arxiv/robustness

papersSEP 11 04:00 UTC

Near-optimal bounds on Lipschitz constants of deep random ReLU networks

This preprint analyzes the ℓ^p-Lipschitz constants of ReLU neural networks mapping from R^d to R when the weights are randomly initialized using a variant of the He scheme, covering p from 1 to infinity. The author derives estimates that are near-optimal, meaning the upper and lower bounds match up to constant factors. The work targets theoretical understanding of how depth and width affect the sensitivity of randomly initialized networks.

research/neural-networks/theory/lipschitz