750 search results - page 70 / 150 » Learning SVMs from Sloppily Labeled Data |
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
NIPS
2008
13 years 10 months ago
2008
The cluster assumption is exploited by most semi-supervised learning (SSL) methods. However, if the unlabeled data is merely weakly related to the target classes, it becomes quest...
AAAI
2006
13 years 10 months ago
2006
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...
NIPS
2007
13 years 10 months ago
2007
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
EMNLP
2007
13 years 10 months ago
2007
We propose a sequence-alignment based method for detecting and disambiguating coordinate conjunctions. In this method, averaged perceptron learning is used to adapt the substituti...