KDD
2000
ACM
13 years 8 months ago
2000
ACM
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
IV
2000
IEEE
13 years 8 months ago
2000
IEEE
We are generating music from a particular view of a multi-dimensional geographic information system (GIS) data set to alert a viewer to the existence of hidden clusters of data po...
CBMS
2003
IEEE
13 years 8 months ago
2003
IEEE
This article addresses 2-dimensional layout of high-dimensional biomedical datasets, which is useful for browsing them efficiently. We employ the Isomap technique, which is based ...
IGIS
1994
13 years 8 months ago
1994
There have been many interpolation methods developed over the years, each with their own problems. One of the biggest limitations in many applications is the non-correspondence of...
VISUALIZATION
1996
IEEE
13 years 8 months ago
1996
IEEE
This can be a costly operation. When the data is arranged according to its three-dimensional coordinates, calculating the contour surfaces requires examining each data cell. Avoidi...
KDD
1998
ACM
13 years 8 months ago
1998
ACM
"Oneperson's noise is another person's signal." For manyapplications, including the detection of credit card frauds and the monitoringof criminal activities in...
PG
1999
IEEE
13 years 8 months ago
1999
IEEE
The objective of this research is to apply the subdivision surface for surface fitting problems when generating surfaces from data points or polyhedral models. The basic idea is t...
ICRA
1999
IEEE
13 years 8 months ago
1999
IEEE
This paper presents a novel method for quickly filtering range data points to make object recognition in large 3D data sets feasible. The general approach, called "3D cueing,...
ICCS
2001
Springer
13 years 9 months ago
2001
Springer
Many surfaces can be modeled by interpolating data points digitized from existing products. But the digitized data points could have measuring errors. To adjust the points, fairing...
WAIM
2009
Springer
13 years 9 months ago
2009
Springer
In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this ...