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» Approximation Methods for Supervised Learning
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COLING
2000
13 years 11 months ago
Automatic Text Categorization by Unsupervised Learning
The goal of text categorization is to classify documents into a certain number of pre-defined categories. The previous works in this area have used a large number of labeled train...
Youngjoong Ko, Jungyun Seo
ICIP
2008
IEEE
14 years 11 months ago
Supervised image segmentation via ground truth decomposition
This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning al...
Ilya Levner, Russell Greiner, Hong Zhang
ICML
2006
IEEE
14 years 10 months ago
Constructing informative priors using transfer learning
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
Rajat Raina, Andrew Y. Ng, Daphne Koller
ACL
2003
13 years 11 months ago
Syntactic Features and Word Similarity for Supervised Metonymy Resolution
We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-mo...
Malvina Nissim, Katja Markert
ITCC
2002
IEEE
14 years 2 months ago
Improve Precategorized Collection Retrieval by Using Supervised Term Weighting Schemes
The emergence of the world-wide-web has led to an increased interest in methods for searching for information. A key characteristic of many of the online document collections is t...
Ying Zhao, George Karypis