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EDM
2009
116views Data Mining» more  EDM 2009»
13 years 7 months ago
Determining the Significance of Item Order In Randomized Problem Sets
Researchers who make tutoring systems would like to know which sequences of educational content lead to the most effective learning by their students. The majority of data collecte...
Zachary A. Pardos, Neil T. Heffernan
DAGM
2008
Springer
13 years 11 months ago
Learning Visual Compound Models from Parallel Image-Text Datasets
Abstract. In this paper, we propose a new approach to learn structured visual compound models from shape-based feature descriptions. We use captioned text in order to drive the pro...
Jan Moringen, Sven Wachsmuth, Sven J. Dickinson, S...
ICML
2007
IEEE
14 years 10 months ago
On the relation between multi-instance learning and semi-supervised learning
Multi-instance learning and semi-supervised learning are different branches of machine learning. The former attempts to learn from a training set consists of labeled bags each con...
Zhi-Hua Zhou, Jun-Ming Xu
APIN
2002
90views more  APIN 2002»
13 years 9 months ago
Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning
Abstract: Locally weighted learning (LWL) is a class of techniques from nonparametric statistics that provides useful representations and training algorithms for learning about com...
Stefan Schaal, Christopher G. Atkeson, Sethu Vijay...
AAAI
2006
13 years 11 months ago
Unsupervised Order-Preserving Regression Kernel for Sequence Analysis
In this work, a generalized method for learning from sequence of unlabelled data points based on unsupervised order-preserving regression is proposed. Sequence learning is a funda...
Young-In Shin