| Learning curves for the multi-class teacher–student perceptron E Cornacchia, F Mignacco, R Veiga, C Gerbelot, B Loureiro, L Zdeborová Machine Learning: Science and Technology 4 (1), 015019, 2023 | 17 | 2023 |
| An initial alignment between neural network and target is needed for gradient descent to learn E Abbe, E Cornacchia, J Hazla, C Marquis International Conference on Machine Learning, 33-52, 2022 | 15 | 2022 |
| Stochastic block model entropy and broadcasting on trees with survey E Abbe, E Cornacchia, Y Gu, Y Polyanskiy Conference on Learning Theory, 1-25, 2021 | 15 | 2021 |
| Learning to reason with neural networks: Generalization, unseen data and boolean measures E Abbe, S Bengio, E Cornacchia, J Kleinberg, A Lotfi, M Raghu, C Zhang Advances in Neural Information Processing Systems 35, 2709-2722, 2022 | 13 | 2022 |
| A mathematical model for curriculum learning for parities E Cornacchia, E Mossel International Conference on Machine Learning, 6402-6423, 2023 | 8* | 2023 |
| Provable advantage of curriculum learning on parity targets with mixed inputs E Abbe, E Cornacchia, A Lotfi Advances in Neural Information Processing Systems 36, 24291-24321, 2023 | 7 | 2023 |
| Intransitive dice tournament is not quasirandom E Cornacchia, J Hązła arXiv preprint arXiv:2011.10067, 2020 | 7 | 2020 |
| Polarization in attraction-repulsion models E Cornacchia, N Singer, E Abbe 2020 IEEE International Symposium on Information Theory (ISIT), 2765-2770, 2020 | 4 | 2020 |
| Theory and applications of the Sum-Of-Squares technique F Bach, E Cornacchia, L Pesce, G Piccioli arXiv preprint arXiv:2306.16255, 2023 | 1 | 2023 |
| Regularization by Misclassification in ReLU Neural Networks E Cornacchia, J Hązła, I Nachum, A Yehudayoff arXiv preprint arXiv:2111.02154, 2021 | 1 | 2021 |
| Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks E Cornacchia EPFL, 2023 | | 2023 |
