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06/17/2023
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions
Reinforcement learning (RL) algorithms have proven transformative in a r...
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03/02/2023
Optimal transfer protocol by incremental layer defrosting
Transfer learning is a powerful tool enabling model training with limite...
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05/31/2022
Inducing bias is simpler than you think
Machine learning may be oblivious to human bias but it is not immune to ...
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05/18/2022
Maslow's Hammer for Catastrophic Forgetting: Node Re-Use vs Node Activation
Continual learning - learning new tasks in sequence while maintaining pe...
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06/15/2021
An Analytical Theory of Curriculum Learning in Teacher-Student Networks
In humans and animals, curriculum learning – presenting data in a curate...
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06/09/2021
Probing transfer learning with a model of synthetic correlated datasets
Transfer learning can significantly improve the sample efficiency of neu...
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02/23/2021
Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problem
When optimizing over loss functions it is common practice to use momentu...
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09/20/2020
Epidemic mitigation by statistical inference from contact tracing data
Contact-tracing is an essential tool in order to mitigate the impact of ...
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06/27/2020
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions
We study the dynamics of optimization and the generalization properties ...
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06/24/2020
Winning the competition: enhancing counter-contagion in SIS-like epidemic processes
In this paper we consider the epidemic competition between two generic d...
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06/12/2020
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval
Despite the widespread use of gradient-based algorithms for optimizing h...
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01/02/2020
Thresholds of descending algorithms in inference problems
We review recent works on analyzing the dynamics of gradient-based algor...
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07/18/2019
Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model
Gradient-based algorithms are effective for many machine learning tasks,...
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02/01/2019
Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model
In this work we analyse quantitatively the interplay between the loss la...
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12/21/2018