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CEAS
2007
Springer
15 years 6 months ago
Online Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
D. Sculley
AAAI
1998
15 years 3 months ago
Learning to Classify Text from Labeled and Unlabeled Documents
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
177
Voted
DATAMINE
2010
161views more  DATAMINE 2010»
14 years 12 months ago
Predicting labels for dyadic data
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
Aditya Krishna Menon, Charles Elkan
ICCV
2009
IEEE
16 years 6 months ago
Sparsity Induced Similarity Measure for Label Propagation
Graph-based semi-supervised learning has gained considerable interests in the past several years thanks to its effectiveness in combining labeled and unlabeled data through labe...
Hong Cheng, Zicheng Liu, Jie Yang
171
Voted
ECCV
2010
Springer
15 years 16 days ago
Supervised Label Transfer for Semantic Segmentation of Street Scenes
In this paper, we propose a robust supervised label transfer method for the semantic segmentation of street scenes. Given an input image of street scene, we first find multiple ima...
Honghui Zhang, Jianxiong Xiao, Long Quan