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» Learning SVMs from Sloppily Labeled Data
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FLAIRS
2006
13 years 9 months ago
Corpus Based Unsupervised Labeling of Documents
Text categorization involves mapping of documents to a fixed set of labels. A similar but equally important problem is that of assigning labels to large corpora. With a deluge of ...
Delip Rao, Deepak P, Deepak Khemani
CVPR
2007
IEEE
14 years 10 months ago
Learning Color Names from Real-World Images
Within a computer vision context color naming is the action of assigning linguistic color labels to image pixels. In general, research on color naming applies the following paradi...
Joost van de Weijer, Cordelia Schmid, Jakob J. Ver...
ACL
2006
13 years 9 months ago
Using Machine-Learning to Assign Function Labels to Parser Output for Spanish
Data-driven grammatical function tag assignment has been studied for English using the Penn-II Treebank data. In this paper we address the question of whether such methods can be ...
Grzegorz Chrupala, Josef van Genabith
ICML
2007
IEEE
14 years 8 months ago
Self-taught learning: transfer learning from unlabeled data
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
ECML
2006
Springer
13 years 11 months ago
Graph Based Semi-supervised Learning with Sharper Edges
In many graph-based semi-supervised learning algorithms, edge weights are assumed to be fixed and determined by the data points' (often symmetric) relationships in input space...
Hyunjung Shin, N. Jeremy Hill, Gunnar Rätsch