Overparametrization bends the landscape: BBP transitions at initialization in simple Neural Networks

ICLROral2026

Authors
Brandon Livio Annesi, Dario Bocchi, Chiara Cammarota
Affiliation
University of Roma "La Sapienza"
Venue
ICLR 2026
Track
Oral

TL;DR

We quantitatively analyze how overparametrization reshapes the high-dimensional loss landscape of a teacher–student setup in random positions, showing it can anticipate and qualitatively alter transitions between successful and failed signal recovery…

Opening excerpt from the authors’ abstract. source

Read the paper

← All ICLR 2026 Oral papers · Browse the whole archive