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» A Preference Model for Structured Supervised Learning Tasks
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PR
2010
186views more  PR 2010»
14 years 8 months ago
Feature extraction by learning Lorentzian metric tensor and its extensions
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Risheng Liu, Zhouchen Lin, Zhixun Su, Kewei Tang
ICML
2006
IEEE
15 years 10 months ago
Collaborative ordinal regression
Ordinal regression has become an effective way of learning user preferences, but most of research only focuses on single regression problem. In this paper we introduce collaborati...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
JMLR
2010
155views more  JMLR 2010»
14 years 8 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
ISBI
2002
IEEE
15 years 10 months ago
Statistical shape model for automatic skull-stripping of brain images
This paper presents a statistical shape model for automatic skull stripping of MR brain images. A surface model of the brain boundary is hierarchically represented by a set of ove...
Zhiqiang Lao, Dinggang Shen, Christos Davatzikos
BILDMED
2006
120views Algorithms» more  BILDMED 2006»
14 years 11 months ago
Towards Automatic Segmentation of Serial High-Resolution Images
Developing barley grains are to be visualised by a 4-D model, in which spatiotemporal experimental data can be integrated. The most crucial task lies in the automation of the exten...
Cornelia Brüß, Marc Strickert, Udo Seif...