arXiv Machine Learning By Anda Skeja, Daniel Guti\'errez Espinoza, Fiona Skerman, Alexander S. Wein

Sharp Low-Degree Thresholds for Planted-vs-Planted Testing

Read the original on arXiv Machine Learning →

arXiv:2606. 05266v1 Announce Type: new Abstract: We establish the first sharp thresholds for low-degree polynomial tests in planted-vs-planted settings, where the goal is to determine with vanishing error which of two structured planted mechanisms generated the observed data.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning
Jun 18

Robust Detection of Planted Subgraphs in Semi-Random Models

arXiv:2508. 02158v2 Announce Type: replace-cross Abstract: Detection of planted subgraphs in Erd\"os-R\'enyi random graphs has been extensively studied, leading to a rich body of results characterizing both statistical and computational thresholds.

By Dor Elimelech, Wasim Huleihel