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» Learning from Highly Structured Data by Decomposition
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JMLR
2010
101views more  JMLR 2010»
14 years 4 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
ICPR
2010
IEEE
15 years 4 months ago
A Bound on the Performance of LDA in Randomly Projected Data Spaces
We consider the problem of classification in nonadaptive dimensionality reduction. Specifically, we bound the increase in classification error of Fisher’s Linear Discriminant...
Robert John Durrant, Ata Kaban
87
Voted
JITECH
2010
106views more  JITECH 2010»
14 years 8 months ago
Patterns and structures of intra-organizational learning networks within a knowledge-intensive organization
This paper employs the network perspective to study patterns and structures of intraorganizational learning networks. The theoretical background draws from cognitive theories, the...
Miha Skerlavaj, Vlado Dimovski, Kevin C. Desouza
ICCS
2009
Springer
15 years 4 months ago
High Frequency Assessment from Multiresolution Analysis
We propose a method for the assessment and visualization of high frequency regions of a multiresolution image. We combine both orientation tensor and multiresolution analysis to gi...
Tássio Knop de Castro, Eder de Almeida Pere...
70
Voted
IWANN
2009
Springer
15 years 4 months ago
On the Bond Graphs in the Delaunay-Tetrahedra of the Simplicial Decomposition of Spatial Protein Structures
The examination of straightforwardly definable discrete structures in nucleic acids and proteins turned out to be perhaps the most important development in our present knowledge a...
Rafael Ördög, Vince Grolmusz