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ICASSP
2009
IEEE
12 years 8 days ago
An information geometric approach to supervised dimensionality reduction
Due to the curse of dimensionality, high-dimensional data is often pre-processed with some form of dimensionality reduction for the classification task. Many common methods of su...
Kevin M. Carter, Raviv Raich, Alfred O. Hero
IRI
2007
IEEE
11 years 12 months ago
Enhancing Text Analysis via Dimensionality Reduction
Many applications require analyzing vast amounts of textual data, but the size and inherent noise of such data can make processing very challenging. One approach to these issues i...
David G. Underhill, Luke McDowell, David J. Marche...
RSS
2007
152views Robotics» more  RSS 2007»
11 years 7 months ago
Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
SAC
2006
ACM
11 years 11 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
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