221 search results - page 36 / 45 » Learning from Labeled and Unlabeled Data Using Random Walks |
IJCV
2006
13 years 7 months ago
2006
In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
ICML
2002
IEEE
14 years 8 months ago
2002
IEEE
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
IDEAL
2009
Springer
14 years 2 months ago
2009
Springer
Abstract. Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, usef...
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
We propose a new active learning algorithm to address the problem of selecting a limited subset of utterances for transcribing from a large amount of unlabeled utterances so that ...
ICCV
2003
IEEE
14 years 9 months ago
2003
IEEE
In this work we present Discriminative Random Fields (DRFs), a discriminative framework for the classification of image regions by incorporating neighborhood interactions in the l...