7 citations · 11 across the 3 of their papers we have counts for
4 papers · 1 filter
Visual processing in context of reinforcement learning
Hlynur Davíð Hlynsson
Although deep reinforcement learning (RL) has recently enjoyed many successes, its methods are still data inefficient, which makes solving numerous problems prohibitively expensive…
Measuring the Data Efficiency of Deep Learning Methods
Hlynur Davíð Hlynsson, Alberto N. Escalante-B., Laurenz Wiskott
In this paper, we propose a new experimental protocol and use it to benchmark the data efficiency --- performance as a function of training set size --- of two deep learning algori…
Learning gradient-based ICA by neurally estimating mutual information
Hlynur Davíð Hlynsson, Laurenz Wiskott
Several methods of estimating the mutual information of random variables have been developed in recent years. They can prove valuable for novel approaches to learning statistically…
Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening
Merlin Schüler, Hlynur Davíð Hlynsson, Laurenz Wiskott
We propose Power Slow Feature Analysis, a gradient-based method to extract temporally slow features from a high-dimensional input stream that varies on a faster time-scale, as a va…