71 search results - page 2 / 15 » Learning low dimensional predictive representations |
CVPR
2007
IEEE
14 years 7 months ago
2007
IEEE
We present an algorithm, Hierarchical ISOmetric SelfOrganizing Map (H-ISOSOM), for a concise, organized manifold representation of complex, non-linear, large scale, high-dimension...
NN
2008
Springer
13 years 5 months ago
2008
Springer
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
A novel approach to scene categorization is proposed. Similar to previous works of [11, 15, 3, 12], we introduce an intermediate space, based on a low dimensional semantic "t...
AAAI
2008
13 years 8 months ago
2008
Matrix factorization algorithms are frequently used in the machine learning community to find low dimensional representations of data. We introduce a novel generative Bayesian pro...
NIPS
2008
13 years 7 months ago
2008
Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...