3 papers
cs.LG2026
On the origin of neural scaling laws: from random graphs to natural language
Maissam Barkeshli, Alberto Alfarano, Andrey Gromov
Scaling laws have played a major role in the modern AI revolution, providing practitioners predictive power over how the model performance will improve with increasing data, comput…
cs.LG2025
TAPAS: Datasets for Learning the Learning with Errors Problem
Eshika Saxena, Alberto Alfarano, François Charton +2
AI-powered attacks on Learning with Errors (LWE), an important hard math problem in post-quantum cryptography, rival or outperform "classical" attacks on LWE under certain paramete…
cs.CV2024
STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing
Andrea Alfarano, Alberto Alfarano, Linda Friso +3
Spatio-Temporal predictive Learning is a self-supervised learning paradigm that enables models to identify spatial and temporal patterns by predicting future frames based on past f…