25 search results - page 2 / 5 » Learning Deep Neural Networks for High Dimensional Output Pr... |
ICANN
2009
Springer
14 years 2 days ago
2009
Springer
Learning to solve small instances of a problem should help in solving large instances. Unfortunately, most neural network architectures do not exhibit this form of scalability. Our...
ICMLA
2010
13 years 5 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...
GRC
2010
IEEE
13 years 8 months ago
2010
IEEE
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
BMCBI
2010
13 years 7 months ago
2010
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
ICDAR
2007
IEEE
14 years 1 months ago
2007
IEEE
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...