We discuss probabilistic neural network models for unsupervised learning...
Learning is a distinctive feature of intelligent behaviour. High-through...
We study a generic ensemble of deep belief networks which is parametrize...
Finding the best model that describes a high dimensional dataset, is a
d...
New researchers are usually very curious about the recipe that could
acc...
We discuss work extraction from classical information engines (e.g.,
Szi...
The hardware and software foundations laid in the first half of the 20th...
We investigate the complexity of logistic regression models which is def...
Learning from the data, in Minimum Description Length (MDL), is equivale...
A `peer-review system' in the context of judging research contributions,...
Simple models, in information theoretic terms, are those with a small
st...
We propose a method for recovering the structure of a sparse undirected
...