Confidence-weighted online learning is a generalization of margin-based learning of linear classifiers in which the margin constraint is replaced by a ...
Abstract. We introduce confidence-weighted linear clas- sifiers, which add parameter confidence infor- mation to linear classifiers. Online learners.
Missing: Categorization. | Show results with:Categorization.
Weight confidence is formalized with a Gaussian distribution over weight vectors, which is updated for each new training example so that the probability of ...
We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers.
Online active classification via margin-based and feature-based label queries · Learning Sparse Confidence-Weighted Classifier on Very High Dimensional Data.
Abstract We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers. Online learners in this setting ...
Fingerprint. Dive into the research topics of 'Confidence-weighted linear classification for text categorization'. Together they form a unique fingerprint.
Abstract We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers.
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Oct 22, 2024 · Confidence-weighted online learning is a generalization of margin-based learning of linear classifiers in which the margin constraint is ...
We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers. Online learners in this setting ...
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