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» Isosurfaces on Optimal Regular Samples
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KDD
2006
ACM
149views Data Mining» more  KDD 2006»
14 years 6 months ago
Regularized discriminant analysis for high dimensional, low sample size data
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Jieping Ye, Tie Wang
TSP
2008
116views more  TSP 2008»
13 years 5 months ago
Nonideal Sampling and Regularization Theory
Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant" space, wh...
Sathish Ramani, Dimitri Van De Ville, Thierry Blu,...
VISUALIZATION
2003
IEEE
13 years 11 months ago
A Frequency-Sensitive Point Hierarchy for Images and Volumes
This paper introduces a method for converting an image or volume sampled on a regular grid into a space-efficient irregular point hierarchy. The conversion process retains the ori...
Tomihisa Welsh, Klaus Mueller
TIP
2010
155views more  TIP 2010»
13 years 4 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
TMI
2010
112views more  TMI 2010»
13 years 4 months ago
Regularized Interpolation for Noisy Images
Abstract—Interpolation is the means by which a continuouslydefined model is fit to discrete data samples. When the data samples are exempt of noise, it seems desirable to build...
Sathish Ramani, Philippe Thévenaz, Michael ...