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» Ensemble Learning Based on Multi-Task Class Labels
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CVPR
2007
IEEE
14 years 9 months ago
Region Classification with Markov Field Aspect Models
Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-offeature approaches label each pixel or patch independently. More adv...
Jakob J. Verbeek, Bill Triggs
ECAI
2000
Springer
13 years 11 months ago
Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations
Abstract. We are interested in the relationship between learning efficiency and representation in the case of supervised neural networks for pattern classification trained by conti...
Marco Gori, Paolo Frasconi, Alessandro Sperduti
WWW
2008
ACM
14 years 8 months ago
Can chinese web pages be classified with english data source?
As the World Wide Web in China grows rapidly, mining knowledge in Chinese Web pages becomes more and more important. Mining Web information usually relies on the machine learning ...
Xiao Ling, Gui-Rong Xue, Wenyuan Dai, Yun Jiang, Q...
ICML
2003
IEEE
14 years 8 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
ECCV
2010
Springer
13 years 7 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof