45 search results - page 3 / 9 » On Feature Selection, Bias-Variance, and Bagging |
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge numbers of features. Most previous studies found that the major...
ICB
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. State-of-the-art palmprint recognition algorithms achieve high accuracy based on component based texture analysis. However, they are still sensitive to local variations o...
MIRAGE
2009
Springer
13 years 11 months ago
2009
Springer
In this paper we propose a novel framework for 3D object categorization. The object is modeled it in terms of its sub-parts as an histogram of 3D visual word occurrences. We introd...
CVPR
2009
IEEE
14 years 11 months ago
2009
IEEE
Multiple-instance Learning (MIL) is a new paradigm
of supervised learning that deals with the classification of
bags. Each bag is presented as a collection of instances
from whi...
ICMCS
2005
IEEE
13 years 10 months ago
2005
IEEE
In this work we strive to find an optimal set of acoustic features for the discrimination of speech, monophonic singing, and polyphonic music to robustly segment acoustic media st...