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» Approximation Methods for Supervised Learning
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AMT
2006
Springer
147views Multimedia» more  AMT 2006»
14 years 15 days ago
Semi-Supervised Text Classification Using Positive and Unlabeled Data
Text classification using positive and unlabeled data refers to the problem of building text classifier using positive documents (P) of one class and unlabeled documents (U) of man...
Shuang Yu, Xueyuan Zhou, Chunping Li
INTERSPEECH
2010
13 years 3 months ago
Exploring speaker characteristics for meeting summarization
In this paper, we investigate using meeting-specific characteristics to improve extractive meeting summarization, in particular, speaker-related attributes (such as verboseness, g...
Fei Liu, Yang Liu
IJSI
2008
156views more  IJSI 2008»
13 years 8 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
KCAP
2011
ACM
12 years 11 months ago
Integrating knowledge capture and supervised learning through a human-computer interface
Some supervised-learning algorithms can make effective use of domain knowledge in addition to the input-output pairs commonly used in machine learning. However, formulating this a...
Trevor Walker, Gautam Kunapuli, Noah Larsen, David...
ICCV
2005
IEEE
14 years 10 months ago
A Supervised Learning Framework for Generic Object Detection in Images
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
Saad Ali, Mubarak Shah