90 search results - page 6 / 18 » Semi-Supervised Learning with Very Few Labeled Training Exam... |
CVPR
2006
IEEE
14 years 8 months ago
2006
IEEE
Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this pr...
SIGIR
2010
ACM
13 years 10 months ago
2010
ACM
We investigate the problem of learning document classifiers in a multilingual setting, from collections where labels are only partially available. We address this problem in the ...
KDD
2002
ACM
14 years 7 months ago
2002
ACM
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
CVPR
2007
IEEE
14 years 8 months ago
2007
IEEE
Our goal is to circumvent one of the roadblocks to using existing approaches for single-view recognition for achieving multi-view recognition, namely, the need for sufficient trai...
HIS
2008
13 years 8 months ago
2008
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...