Antonin de Courcel (ENS) “Effective models in high-dimensional unstable regimes: optimization dynamics at the edge of stability” Nicolas Mil-Homens Cavaco (Louvain) “Expressivity of lazy sinusoidal neural networks: A joint kernel-based and frame-theoretic approach” Antonin de Courcel (DMA) “Effective models in high-dimensional unstable regimes: optimization dynamics at the edge of stability” Nicolas Mil-Homens Cavaco (Université catholique de Louvain) “Expressivity of lazy sinusoidal neural networks: A joint kernel-based and frame-theoretic approach”

Our understanding of how neural networks learn from structured data is caught between two extremes: theory largely relies on high-dimensional random data, which lacks any structure, while experiments rely on real-world benchmarks, whose structure is not understood. This talk takes the middle road and works with a synthetic data model that is simple enough to be controlled yet rich enough to be informative. Sequences are generated by a branching process on a tree, so that elements inherit nested correlations across all scales, in a manner reminiscent of language or images, […]