23 search results - page 4 / 5 » An analysis of how training data complexity affects the near... |
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
ICCV
2009
IEEE
15 years 12 days ago
2009
IEEE
Similarity metrics that are learned from labeled training
data can be advantageous in terms of performance
and/or efficiency. These learned metrics can then be used
in conjuncti...
ACCV
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
ECCV
2006
Springer
13 years 11 months ago
2006
Springer
While learning ensembles have been widely used for various pattern recognition tasks, surprisingly, they have found limited application in problems related to medical image analysi...
ECCV
2008
Springer
14 years 9 months ago
2008
Springer
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...