Stefano Sarao Mannelli
My research focuses on analysing machine learning problems using a model-based approach, where the complexity of the problem is reduced to obtain a parsimonious solvable model that still captures the phenomenon of interest. In my previous works, I applied several variations of this approach to study problems in learning, such as transfer learning, continual learning, and curriculum learning
Visar 5 publikationer
A THEORY OF INITIALISATION'S IMPACT ON SPECIALISATION
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory
Bias-inducing geometries: An exactly solvable data model with fairness implications
Optimal protocols for continual learning via statistical physics and control theory
RL Perceptron: Generalization Dynamics of Policy Learning in High Dimensions
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