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» Support Vector Machines with Example Dependent Costs
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ICML
2003
IEEE
14 years 9 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
KDD
2000
ACM
137views Data Mining» more  KDD 2000»
14 years 17 days ago
Alpha seeding for support vector machines
Dennis DeCoste, Kiri Wagstaff
CASCON
2001
148views Education» more  CASCON 2001»
13 years 10 months ago
Email classification with co-training
The main problems in text classification are lack of labeled data, as well as the cost of labeling the unlabeled data. We address these problems by exploring co-training - an algo...
Svetlana Kiritchenko, Stan Matwin
NIPS
2003
13 years 10 months ago
Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
The decision functions constructed by support vector machines (SVM’s) usually depend only on a subset of the training set—the so-called support vectors. We derive asymptotical...
Ingo Steinwart
ICML
2004
IEEE
14 years 9 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...