144 search results - page 6 / 29 » Combining Active Learning and Dynamic Dimensionality Reducti... |
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
We describe a probabilistic framework for recognizing human activities in monocular video based on simple silhouette observations in this paper. The methodology combines kernel pr...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
AI
2004
Springer
13 years 7 months ago
2004
Springer
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
AAAI
2008
13 years 10 months ago
2008
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
CVPR
2010
IEEE
14 years 4 months ago
2010
IEEE
We present an active learning framework to simultaneously learn appearance and contextual models for scene understanding tasks (multi-class classification). Existing multi-class a...