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» Lossy Reduction for Very High Dimensional Data
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JEA
2008
112views more  JEA 2008»
14 years 11 months ago
Dynamic spatial approximation trees
The Spatial Approximation Tree (sa-tree) is a recently proposed data structure for searching in metric spaces. It has been shown that it compares favorably against alternative data...
Gonzalo Navarro, Nora Reyes
ICML
2005
IEEE
16 years 19 days ago
Multimodal oriented discriminant analysis
Linear discriminant analysis (LDA) has been an active topic of research during the last century. However, the existing algorithms have several limitations when applied to visual d...
Fernando De la Torre, Takeo Kanade
ICDE
1997
IEEE
108views Database» more  ICDE 1997»
16 years 1 months ago
Titan: A High-Performance Remote Sensing Database
There are two major challenges for a high-performance remote-sensing database. First, it must provide low-latency retrieval of very large volumes of spatio-temporaldata. This requ...
Chialin Chang, Bongki Moon, Anurag Acharya, Carter...
SSDBM
2006
IEEE
123views Database» more  SSDBM 2006»
15 years 5 months ago
Mining Hierarchies of Correlation Clusters
The detection of correlations between different features in high dimensional data sets is a very important data mining task. These correlations can be arbitrarily complex: One or...
Elke Achtert, Christian Böhm, Peer Kröge...
BMCBI
2006
202views more  BMCBI 2006»
14 years 12 months ago
Spectral embedding finds meaningful (relevant) structure in image and microarray data
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...