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» Dimensionality reduction and generalization
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HICSS
2007
IEEE
137views Biometrics» more  HICSS 2007»
14 years 4 months ago
Essential Dimensions of Latent Semantic Indexing (LSI)
Latent Semantic Indexing (LSI) is commonly used to match queries to documents in information retrieval applications. LSI has been shown to improve retrieval performance for some, ...
April Kontostathis
AIPR
2003
IEEE
14 years 3 months ago
Band Selection Using Independent Component Analysis for Hyperspectral Image Processing
Although hyperspectral images provide abundant information about objects, their high dimensionality also substantially increases computational burden. Dimensionality reduction off...
Hongtao Du, Hairong Qi, Xiaoling Wang, Rajeev Rama...
ICML
2010
IEEE
13 years 11 months ago
Local Minima Embedding
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
Minyoung Kim, Fernando De la Torre
ENGL
2007
101views more  ENGL 2007»
13 years 10 months ago
Multiresolution Knowledge Mining using Wavelet Transform
— Most research in Knowledge Mining deal with the basic models like clustering, classification, regression, association rule mining and so on. In the process of quest for knowled...
R. Pradeep Kumar, P. Nagabhushan
IBPRIA
2003
Springer
14 years 3 months ago
Supervised Locally Linear Embedding Algorithm for Pattern Recognition
The dimensionality of the input data often far exceeds their intrinsic dimensionality. As a result, it may be difficult to recognize multidimensional data, especially if the number...
Olga Kouropteva, Oleg Okun, Matti Pietikäinen