Troiani, Emanuele

8 publications

NeurIPS 2025 Bayes Optimal Learning of Attention-Indexed Models Fabrizio Boncoraglio, Emanuele Troiani, Vittorio Erba, Lenka Zdeborova

AISTATS 2025 Fundamental Computational Limits of Weak Learnability in High-Dimensional Multi-Index Models Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborova, Bruno Loureiro, Florent Krzakala

ICML 2025 Fundamental Limits of Learning in Sequence Multi-Index Models and Deep Attention Networks: High-Dimensional Asymptotics and Sharp Thresholds Emanuele Troiani, Hugo Cui, Yatin Dandi, Florent Krzakala, Lenka Zdeborova

NeurIPS 2025 The Nuclear Route: Sharp Asymptotics of ERM in Overparameterized Quadratic Networks Vittorio Erba, Emanuele Troiani, Lenka Zdeborova, Florent Krzakala

AISTATS 2024 Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of Outliers Matteo Vilucchio, Emanuele Troiani, Vittorio Erba, Florent Krzakala

NeurIPS 2024 Bayes-Optimal Learning of an Extensive-Width Neural Network from Quadratically Many Samples Antoine Maillard, Emanuele Troiani, Simon Martin, Lenka Zdeborová, Florent Krzakala

ICMLW 2024 Fundamental Limits of Weak Learnability in High-Dimensional Multi-Index Models Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborova, Bruno Loureiro, Florent Krzakala

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, Luca Pesce, Lenka Zdeborova, Florent Krzakala