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» On Kernel Methods for Relational Learning
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ICML
2005
IEEE
16 years 4 months ago
Analysis and extension of spectral methods for nonlinear dimensionality reduction
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
Fei Sha, Lawrence K. Saul
112
Voted
CE
2007
99views more  CE 2007»
15 years 3 months ago
Contextual learning theory: Concrete form and a software prototype to improve early education
In Ôcontextual learning theoryÕ three types of contextual conditions (differentiation of learning procedures and materials, integrated ICT support, and improvement of developme...
Ton Mooij
132
Voted

Publication
173views
14 years 2 months ago
Max-Flow Segmentation of the Left Ventricle by Recovering Subject-Specific Distributions via a Bound of the Bhattacharyya Measur
This study investigates fast detection of the left ventricle (LV) endo- and epicardium boundaries in a cardiac magnetic resonance (MR) sequence following the optimization of two or...
Ismail Ben Ayed, Hua-mei Chen, Kumaradevan Punitha...
139
Voted
DAGM
2009
Springer
15 years 10 months ago
Active Structured Learning for High-Speed Object Detection
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
Christoph H. Lampert, Jan Peters
DIS
2007
Springer
15 years 9 months ago
A Hilbert Space Embedding for Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
Alexander J. Smola, Arthur Gretton, Le Song, Bernh...