16 search results - page 2 / 4 » A Bayesian Approach to Unsupervised Feature Selection and De... |
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
NIPS
2007
13 years 6 months ago
2007
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
IROS
2008
IEEE
13 years 11 months ago
2008
IEEE
—This paper presents an alternative formulation for the Bayesian feature-based simultaneous localisation and mapping (SLAM) problem, using a random finite set approach. For a fe...
NECO
2011
12 years 11 months ago
2011
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
NLPRS
2001
Springer
13 years 9 months ago
2001
Springer
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...