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ICML
2010
IEEE
13 years 8 months ago
Asymptotic Analysis of Generative Semi-Supervised Learning
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...
COLT
2008
Springer
13 years 9 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál
EMNLP
2010
13 years 5 months ago
Staying Informed: Supervised and Semi-Supervised Multi-View Topical Analysis of Ideological Perspective
With the proliferation of user-generated articles over the web, it becomes imperative to develop automated methods that are aware of the ideological-bias implicit in a document co...
Amr Ahmed, Eric P. Xing
ICPR
2010
IEEE
13 years 9 months ago
SemiCCA: Efficient Semi-Supervised Learning of Canonical Correlations
Canonical correlation analysis (CCA) is a powerful tool for analyzing multi-dimensional paired data. However, CCA tends to perform poorly when the number of paired samples is limit...
Akisato Kimura, Hirokazu Kameoka, Masashi Sugiyama...
TIT
2008
224views more  TIT 2008»
13 years 7 months ago
Graph-Based Semi-Supervised Learning and Spectral Kernel Design
We consider a framework for semi-supervised learning using spectral decomposition-based unsupervised kernel design. We relate this approach to previously proposed semi-supervised l...
Rie Johnson, Tong Zhang