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» Learning to Classify Texts Using Positive and Unlabeled Data
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BMCBI
2006
158views more  BMCBI 2006»
13 years 7 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
ICASSP
2009
IEEE
14 years 2 months ago
Using collective information in semi-supervised learning for speech recognition
Training accurate acoustic models typically requires a large amount of transcribed data, which can be expensive to obtain. In this paper, we describe a novel semi-supervised learn...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
TIP
2008
169views more  TIP 2008»
13 years 7 months ago
Weakly Supervised Learning of a Classifier for Unusual Event Detection
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...
Mark Jager, Christian Knoll, Fred A. Hamprecht
CISSE
2008
Springer
13 years 9 months ago
Sentiment Mining Using Ensemble Classification Models
We live in the information age, where the amount of data readily available already overwhelms our capacity to analyze and absorb it without help from our machines. In particular, ...
Matthew Whitehead, Larry Yaeger
CVPR
2008
IEEE
13 years 7 months ago
Joint learning and dictionary construction for pattern recognition
We propose a joint representation and classification framework that achieves the dual goal of finding the most discriminative sparse overcomplete encoding and optimal classifier p...
Duc-Son Pham, Svetha Venkatesh