16 search results - page 3 / 4 » Learning Deep Boltzmann Machines using Adaptive MCMC |
FPL
2009
Springer
13 years 10 months ago
2009
Springer
Restricted Boltzmann Machines (RBMs) — the building block for newly popular Deep Belief Networks (DBNs) — are a promising new tool for machine learning practitioners. However,...
CVPR
2012
IEEE
11 years 8 months ago
2012
IEEE
A good model of object shape is essential in applications such as segmentation, object detection, inpainting and graphics. For example, when performing segmentation, local constra...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
ICPR
2010
IEEE
13 years 9 months ago
2010
IEEE
Ultrasound has become a useful tool for speech scientists studying mechanisms of language sound production. State-of-the-art methods for extracting tongue contours from ultrasound...
AAAI
2011
12 years 5 months ago
2011
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...