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Contrastive pessimistic likelihood estimation for semi-supervised classification
Marco Loog
Department of Computer Science
36
Citations (Scopus)
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Dive into the research topics of 'Contrastive pessimistic likelihood estimation for semi-supervised classification'. Together they form a unique fingerprint.
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Mathematics
Supervised Classification
100%
Likelihood
58%
Classifier
56%
Estimate
30%
Test Set
21%
Error Rate
19%
Training
17%
Independent Set
16%
Labeling
16%
Parameter Estimation
15%
Objective function
14%
Strictly
12%
Experiment
12%
Demonstrate
10%
Concepts
8%
Form
6%
Engineering & Materials Science
Classifiers
47%
Labeling
21%
Parameter estimation
20%
Experiments
7%