Stefano Sarao Mannelli
I am Stefano Sarao Mannelli, a WASP tunure-track Assistant Professor in the Data Science and AI division in the Computer Science department of Chalmers University of Technology and Gothenburg University. 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 works, I applied several variations of this approach to study problems in learning, such as transfer learning, continual learning, curriculum learning, and bias generation.
Showing 6 publications
A theory of initialisation's impact on specialisation*
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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