75 search results - page 10 / 15 » Sparse Feature Learning for Deep Belief Networks |
89
Voted
FPL
2009
Springer
15 years 2 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,...
KDD
2009
ACM
15 years 4 months ago
2009
ACM
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
IJON
2008
14 years 9 months ago
2008
Image representation has been a key issue in vision research for many years. In order to represent various local image patterns or objects effectively, it is important to study th...