Luca Pesce
Orcid: 0000-0001-9610-2615
According to our database1,
Luca Pesce
authored at least 15 papers
between 2021 and 2025.
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Bibliography
2025
The Computational Advantage of Depth: Learning High-Dimensional Hierarchical Functions with Gradient Descent.
CoRR, February, 2025
A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025
2024
Online Learning and Information Exponents: On The Importance of Batch size, and Time/Complexity Tradeoffs.
CoRR, 2024
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions.
CoRR, 2024
The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation.
Proceedings of the International Conference on Machine Learning, 2023
2022
Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
2021