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» Learning from Highly Structured Data by Decomposition
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UAI
1996
14 years 11 months ago
Learning Bayesian Networks with Local Structure
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Nir Friedman, Moisés Goldszmidt
EDUTAINMENT
2008
Springer
14 years 11 months ago
Reconstruction of Tree Crown Shape from Scanned Data
Reconstruction of a real tree from scattered scanned points is a new challenge in virtual reality. Although many progresses are made on main branch structures and overall shape of ...
Chao Zhu, Xiaopeng Zhang, Bao-Gang Hu, Marc Jaeger
CIKM
2011
Springer
13 years 9 months ago
Semi-supervised multi-task learning of structured prediction models for web information extraction
Extracting information from web pages is an important problem; it has several applications such as providing improved search results and construction of databases to serve user qu...
Paramveer S. Dhillon, Sundararajan Sellamanickam, ...
AH
2008
Springer
15 years 4 months ago
Analysing High-Level Help-Seeking Behaviour in ITSs
Abstract. In this paper, we look at initial results of data mining students’ help-seeking behaviour in two ITSs: SQL-Tutor and EER-Tutor. We categorised help given by these tutor...
Moffat Mathews, Tanja Mitrovic, David Thomson
JMLR
2012
13 years 9 days ago
Transductive Learning of Structural SVMs via Prior Knowledge Constraints
Reducing the number of labeled examples required to learn accurate prediction models is an important problem in structured output prediction. In this paper we propose a new transd...
Chun-Nam Yu