Humans sometimes show sudden improvements in task performance that have ...
Our theoretical understanding of deep learning has not kept pace with it...
Deep neural networks achieve stellar generalisation even when they have
...
Deep neural networks achieve stellar generalisation on a variety of prob...
An extensive body of empirical research has revealed remarkable regulari...
In this work, we propose a new training method for finding minimum weigh...
In this work, we propose a new training method for finding minimum weigh...
Finding parameters that minimise a loss function is at the core of many
...
We perform an average case analysis of the generalization dynamics of la...
Hierarchical reinforcement learning methods offer a powerful means of
pl...
Hierarchical architectures are critical to the scalability of reinforcem...
Continual Learning in artificial neural networks suffers from interferen...
Training neural networks involves solving large-scale non-convex optimiz...
Despite the widespread practical success of deep learning methods, our
t...