19 search results - page 3 / 4 » Learning from data with uncertain labels by boosting credal ... |
ICML
2009
IEEE
14 years 9 months ago
2009
IEEE
We describe a new method for learning the conditional probability distribution of a binary-valued variable from labelled training examples. Our proposed Compositional Noisy-Logica...
CVPR
2008
IEEE
14 years 10 months ago
2008
IEEE
This paper studies image alignment, the problem of learning a shape and appearance model from labeled data and efficiently fitting the model to a non-rigid object with large varia...
KDD
2006
ACM
14 years 9 months ago
2006
ACM
Many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from...
AIPRF
2007
13 years 10 months ago
2007
This paper presents experiments on classifying web pages by genre. Firstly, a corpus of 1539 manually labeled web pages was prepared. Secondly, 502 genre features were selected ba...
ICCV
2007
IEEE
14 years 10 months ago
2007
IEEE
Boosting has been widely applied in computer vision, especially after Viola and Jones's seminal work [23]. The marriage of rectangular features and integral-imageenabled fast...