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» Closed Sets for Labeled Data
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NIPS
2001
13 years 6 months ago
Partially labeled classification with Markov random walks
To classify a large number of unlabeled examples we combine a limited number of labeled examples with a Markov random walk representation over the unlabeled examples. The random w...
Martin Szummer, Tommi Jaakkola
MM
2005
ACM
145views Multimedia» more  MM 2005»
13 years 11 months ago
Multiple instance learning for labeling faces in broadcasting news video
Labeling faces in news video with their names is an interesting research problem which was previously solved using supervised methods that demand significant user efforts on lab...
Jun Yang 0003, Rong Yan, Alexander G. Hauptmann
PKDD
2010
Springer
128views Data Mining» more  PKDD 2010»
13 years 3 months ago
Learning to Tag from Open Vocabulary Labels
Most approaches to classifying media content assume a fixed, closed vocabulary of labels. In contrast, we advocate machine learning approaches which take advantage of the millions...
Edith Law, Burr Settles, Tom M. Mitchell
KDD
2008
ACM
148views Data Mining» more  KDD 2008»
14 years 5 months ago
Get another label? improving data quality and data mining using multiple, noisy labelers
This paper addresses the repeated acquisition of labels for data items when the labeling is imperfect. We examine the improvement (or lack thereof) in data quality via repeated la...
Victor S. Sheng, Foster J. Provost, Panagiotis G. ...
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 5 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang