Sciweavers

114 search results - page 18 / 23
» Nonlinear adaptive distance metric learning for clustering
Sort
View
TKDE
2010
168views more  TKDE 2010»
13 years 5 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
BMCBI
2005
120views more  BMCBI 2005»
13 years 7 months ago
SpectralNET - an application for spectral graph analysis and visualization
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...
CORR
2010
Springer
92views Education» more  CORR 2010»
13 years 4 months ago
Regression on fixed-rank positive semidefinite matrices: a Riemannian approach
The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...
Gilles Meyer, Silvere Bonnabel, Rodolphe Sepulchre
ICIP
2007
IEEE
14 years 9 months ago
Large Scale Learning of Active Shape Models
We propose a framework to learn statistical shape models for faces as piecewise linear models. Specifically, our methodology builds upon primitive active shape models(ASM) to hand...
Atul Kanaujia, Dimitris N. Metaxas
ICML
2008
IEEE
14 years 8 months ago
Nearest hyperdisk methods for high-dimensional classification
In high-dimensional classification problems it is infeasible to include enough training samples to cover the class regions densely. Irregularities in the resulting sparse sample d...
Hakan Cevikalp, Bill Triggs, Robi Polikar