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04/14/2023
Optimal inference of a generalised Potts model by single-layer transformers with factored attention
Transformers are the type of neural networks that has revolutionised nat...
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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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05/26/2022
Gaussian Universality of Linear Classifiers with Random Labels in High-Dimension
While classical in many theoretical settings, the assumption of Gaussian...
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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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02/21/2020
Generalisation error in learning with random features and the hidden manifold model
We study generalised linear regression and classification for a syntheti...
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02/01/2019
Signal propagation in continuous approximations of binary neural networks
The training of stochastic neural network models with binary (±1) weight...
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10/26/2017
On the role of synaptic stochasticity in training low-precision neural networks
Stochasticity and limited precision of synaptic weights in neural networ...
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02/12/2016