arXiv Machine Learning By Saveliy Baturin

From Approximation Rates to Loss-Landscape Barrier Decay in Shallow ReLU Networks

Read the original on arXiv Machine Learning →

arXiv:2602. 17596v2 Announce Type: replace Abstract: We study pathwise connectivity of sublevel sets for one-hidden-layer ReLU networks with constrained first-layer weights and an $\ell_1$ penalty on the output layer.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.