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» Approximation Methods for Supervised Learning
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CVPR
2012
IEEE
11 years 11 months ago
Weakly supervised structured output learning for semantic segmentation
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
ICPR
2010
IEEE
13 years 10 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...
JIDM
2010
90views more  JIDM 2010»
13 years 3 months ago
A Context-Dependent Supervised Learning Approach to Sentiment Detection in Large Textual Databases
Sentiment detection automatically identifies emotions in textual data. The increasing amount of emotive documents available in corporate databases and on the World Wide Web calls f...
Albert Weichselbraun, Stefan Gindl, Arno Scharl
EMNLP
2008
13 years 10 months ago
Joint Unsupervised Coreference Resolution with Markov Logic
Machine learning approaches to coreference resolution are typically supervised, and require expensive labeled data. Some unsupervised approaches have been proposed (e.g., Haghighi...
Hoifung Poon, Pedro Domingos
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
13 years 10 months ago
Semi-Supervised Learning Based on Semiparametric Regularization
Semi-supervised learning plays an important role in the recent literature on machine learning and data mining and the developed semisupervised learning techniques have led to many...
Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Chr...