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» Learning from Labeled and Unlabeled Data Using Random Walks
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CIKM
2000
Springer
14 years 7 days ago
Analyzing the Effectiveness and Applicability of Co-training
Recently there has been significant interest in supervised learning algorithms that combine labeled and unlabeled data for text learning tasks. The co-training setting [1] applie...
Kamal Nigam, Rayid Ghani
WWW
2009
ACM
14 years 8 months ago
Automated construction of web accessibility models from transaction click-streams
Screen readers, the dominant assistive technology used by visually impaired people to access the Web, function by speaking out the content of the screen serially. Using screen rea...
Jalal Mahmud, Yevgen Borodin, I. V. Ramakrishnan, ...
EMMCVPR
1999
Springer
14 years 5 days ago
Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithm
This paper considers the use of the EM-algorithm, combined with mean field theory, for parameter estimation in Markov random field models from unlabelled data. Special attention ...
Markus Svensén, Frithjof Kruggel, D. Yves v...
AAAI
2008
13 years 10 months ago
Semi-Supervised Learning for Blog Classification
Blog classification (e.g., identifying bloggers' gender or age) is one of the most interesting current problems in blog analysis. Although this problem is usually solved by a...
Daisuke Ikeda, Hiroya Takamura, Manabu Okumura
ICPR
2006
IEEE
14 years 9 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden