43 search results - page 3 / 9 » A New Data Selection Principle for Semi-Supervised Increment... |
KDD
2010
ACM
13 years 9 months ago
2010
ACM
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
ICPR
2010
IEEE
13 years 5 months ago
2010
IEEE
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
ACIVS
2009
Springer
13 years 12 months ago
2009
Springer
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...
GREC
2003
Springer
13 years 10 months ago
2003
Springer
This paper presents a method of online sketchy shape recognition that can adapt to different user sketching styles. The adaptation principle is based on incremental active learning...
SETN
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...