Elisabetta Cornacchia

I'm a Postdoctoral Researcher at Inria and École Normale Supérieure (ENS), Paris, working with Prof. Laurent Massoulié. Previously, I spent one year as Postdoctoral Associate at MIT, working with Prof. Elchanan Mossel. I received my PhD in Mathematics from EPFL (Lausanne, Switzerland), where I was advised by Prof. Emmanuel Abbé.

Research Interests: Theory of neural networks, high-dimensional statistics.

Here is a short CV.

Email: eli [dot] cornacchia [at] gmail [dot] com

Publications:

E. Cornacchia, D. Mikulincer, E. Mossel, Low-Dimensional Functions are Efficiently Learnable under Randomly Biased Distributions. COLT 2025. [arXiv]
E. Abbe, E. Cornacchia, J. Hązła, D. Kougang-Yombi, Learning High-Degree Parities: The Crucial Role of the Initialization. ICLR 2025. [arXiv]
F. Bach, E. Cornacchia, L. Pesce, G. Piccioli, Theory and Applications of the Sum-Of-Squares Technique (Les Houches 2022 Lecture Notes). Journal of Statistical Mechanics: Theory and Experiments 2024. [arXiv]
E. Abbe, E. Cornacchia, A. Lotfi. Provable Avantage of Curriculum Learning on Parity Targets with Mixed Inputs. NeurIPS 2023. [arXiv ]
E. Cornacchia, E. Mossel. A Mathematical Model for Curriculum Learning for Parities. ICML 2023. [arXiv]
E. Abbe, S. Bengio, E. Cornacchia, J. Kleinberg, A. Lotfi, M. Raghu, C. Zhang. Learning to reason with neural networks: Generalization, unseen data and Boolean measures. NeurIPS 2022. [arXiv]
E. Abbe, E. Cornacchia, J. Hązła, C. Marquis. An initial alignment between neural network and target is needed for gradient descent to learn. ICML 2022. [arXiv]
E. Cornacchia*, F. Mignacco*, R. Veiga*, C. Gerbelot, B. Loureiro, L. Zdeborova. Learning curves for the multi-class teacher-student perceptron. Machine Learning: Science and Technology, 2022. [arXiv]
E. Abbe, E. Cornacchia, Y. Gu, Y. Polyanskiy. Stochastic block model entropy and broadcasting on trees with survey. COLT 2021 Best Student Paper Award. [arXiv]
E. Cornacchia, J. Hązła. Intransitive dice tournament is not quasirandom. Journal of Combinatorial Theory, 2020 [arXiv, Quanta article].
E. Cornacchia*, N. Singer, E. Abbe. Polarization in attraction-repulsion models. ISIT 2020. [arXiv]

*: denotes equally contributing first authors. In other papers, authors are listed in alphabetical order.

News article:

Quanta Magazine: Mathematicians Roll Dice and Get Rock-Paper-Scissors