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» INSPIRE: A New Method of Mapping Information Spaces
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CVPR
2009
IEEE
16 years 4 months ago
Shared Kernel Information Embedding for Discriminative Inference
Latent Variable Models (LVM), like the Shared-GPLVM and the Spectral Latent Variable Model, help mitigate over- fitting when learning discriminative methods from small or modera...
David J. Fleet, Leonid Sigal, Roland Memisevic
FLAIRS
2003
14 years 11 months ago
Topic Extraction and Extension to Support Concept Mapping
Successful knowledge management may depend not only on knowledge capture, but on knowledge construction—on formulating new and useful knowledge that was not previously available...
David B. Leake, Ana Gabriela Maguitman, Thomas Rei...
NAR
2006
87views more  NAR 2006»
14 years 9 months ago
From genomics to chemical genomics: new developments in KEGG
The increasing amount of genomic and molecular information is the basis for understanding higherorder biological systems, such as the cell and the 15 organism, and their interacti...
Minoru Kanehisa, Susumu Goto, Masahiro Hattori, Ki...
SSD
1999
Springer
106views Database» more  SSD 1999»
15 years 2 months ago
XZ-Ordering: A Space-Filling Curve for Objects with Spatial Extension
There is an increasing need to integrate spatial index structures into commercial database management systems. In geographic information systems (GIS), huge amounts of information ...
Christian Böhm, Gerald Klump, Hans-Peter Krie...
BC
2007
113views more  BC 2007»
14 years 10 months ago
Akaike causality in state space
We present a new approach of explaining partial causality in multivariate fMRI time series by a state space model. A given single time series can be divided into two noise-driven ...
Kin Foon Kevin Wong, Tohru Ozaki