From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks. - Luca Arnaboldi 002; Ludovic Stephan; Florent Krzakala; Bruno Loureiro (COLT, 2023)

Escaping mediocrity: how two-layer networks learn hard single-index models with SGD. - Luca Arnaboldi 002; Florent Krzakala; Bruno Loureiro; Ludovic Stephan (CoRR, 2023)

Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs. - Luca Arnaboldi 002; Yatin Dandi; Florent Krzakala; Bruno Loureiro; Luca Pesce; Ludovic Stephan (ICML, 2024)

The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents. - Yatin Dandi; Emanuele Troiani; Luca Arnaboldi 002; Luca Pesce; Lenka Zdeborová; Florent Krzakala (ICML, 2024)

Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions. - Luca Arnaboldi 002; Yatin Dandi; Florent Krzakala; Luca Pesce; Ludovic Stephan (CoRR, 2024)

Online Learning and Information Exponents: On The Importance of Batch size, and Time/Complexity Tradeoffs. - Luca Arnaboldi 002; Yatin Dandi; Florent Krzakala; Bruno Loureiro; Luca Pesce; Ludovic Stephan (CoRR, 2024)

Asymptotics of SGD in Sequence-Single Index Models and Single-Layer Attention Networks. - Luca Arnaboldi 002; Bruno Loureiro; Ludovic Stephan; Florent Krzakala; Lenka Zdeborová (CoRR, 2025)