75 search results - page 2 / 15 » Sparse Feature Learning for Deep Belief Networks |
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
This paper considers application of Deep Belief Nets (DBNs) to natural language call routing. DBNs have been successfully applied to a number of tasks, including image, audio and ...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...
ICMLA
2010
13 years 2 months ago
2010
Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
JMLR
2012
11 years 7 months ago
2012
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...