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SAC
2005
ACM
14 years 2 months ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra
ICCV
2005
IEEE
14 years 10 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
EMNLP
2007
13 years 10 months ago
Structured Prediction Models via the Matrix-Tree Theorem
This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how p...
Terry Koo, Amir Globerson, Xavier Carreras, Michae...
PPSN
2004
Springer
14 years 2 months ago
Learning Probabilistic Tree Grammars for Genetic Programming
Genetic Programming (GP) provides evolutionary methods for problems with tree representations. A recent development in Genetic Algorithms (GAs) has led to principled algorithms cal...
Peter A. N. Bosman, Edwin D. de Jong
WWW
2007
ACM
14 years 9 months ago
Integrating web directories by learning their structures
Documents in the Web are often organized using category trees by information providers (e.g. CNN, BBC) or search engines (e.g. Google, Yahoo!). Such category trees are commonly kn...
Christopher C. Yang, Jianfeng Lin