Francesca Mignacco

20 papers A* 5Journal 15
YearRankTypeTitle / Venue / Authors
2025 J jnl
A statistical physics framework for optimal learning.
CoRR
Francesca Mignacco, Francesco Mori
2025 J jnl
Analytic theory of dropout regularization.
CoRR
Francesco Mori, Francesca Mignacco
2025 A* conf
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory.
ICLR
Francesco Mori, Stefano Sarao Mannelli, Francesca Mignacco
2024 A* conf
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers.
NeurIPS
Lorenzo Tiberi, Francesca Mignacco, Kazuki Irie, Haim Sompolinsky
2024 J jnl
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers.
CoRR
Lorenzo Tiberi, Francesca Mignacco, Kazuki Irie, Haim Sompolinsky
2024 A* conf
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization.
ICLR
Ravi Francesco Srinivasan, Francesca Mignacco, Martino Sorbaro, Maria Refinetti, Avi Cooper, Gabriel Kreiman, Giorgia Dellaferrera
2024 J jnl
Nonlinear classification of neural manifolds with contextual information.
CoRR
Francesca Mignacco, Chi-Ning Chou, SueYeon Chung
2024 J jnl
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory.
CoRR
Francesco Mori, Stefano Sarao Mannelli, Francesca Mignacco
2024 J jnl
Rigorous Dynamical Mean-Field Theory for Stochastic Gradient Descent Methods.
SIAM J. Math. Data Sci.
Cédric Gerbelot, Emanuele Troiani, Francesca Mignacco, Florent Krzakala, Lenka Zdeborová
2023 J jnl
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization.
CoRR
Ravi Francesco Srinivasan, Francesca Mignacco, Martino Sorbaro, Maria Refinetti, Avi Cooper, Gabriel Kreiman, Giorgia Dellaferrera
2023 J jnl
Learning curves for the multi-class teacher-student perceptron.
Mach. Learn. Sci. Technol.
Elisabetta Cornacchia, Francesca Mignacco, Rodrigo Veiga, Cédric Gerbelot, Bruno Loureiro, Lenka Zdeborová
2022 J jnl
Learning curves for the multi-class teacher-student perceptron.
CoRR
Elisabetta Cornacchia, Francesca Mignacco, Rodrigo Veiga, Cédric Gerbelot, Bruno Loureiro, Lenka Zdeborová
2022 J jnl
Rigorous dynamical mean field theory for stochastic gradient descent methods.
CoRR
Cédric Gerbelot, Emanuele Troiani, Francesca Mignacco, Florent Krzakala, Lenka Zdeborová
2021 J jnl
Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem.
CoRR
Francesca Mignacco, Pierfrancesco Urbani, Lenka Zdeborová
2021 J jnl
Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem.
Mach. Learn. Sci. Technol.
Francesca Mignacco, Pierfrancesco Urbani, Lenka Zdeborová
2021 J jnl
The effective noise of Stochastic Gradient Descent.
CoRR
Francesca Mignacco, Pierfrancesco Urbani
2020 A* conf
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification.
NeurIPS
Francesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2020 J jnl
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification.
CoRR
Francesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2020 A* conf
The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture.
ICML
Francesca Mignacco, Florent Krzakala, Yue M. Lu, Pierfrancesco Urbani, Lenka Zdeborová
2020 J jnl
The role of regularization in classification of high-dimensional noisy Gaussian mixture.
CoRR
Francesca Mignacco, Florent Krzakala, Yue M. Lu, Lenka Zdeborová