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» Dimensionality reduction and generalization
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JGO
2008
95views more  JGO 2008»
13 years 10 months ago
Generalized Semi-Infinite Programming: on generic local minimizers
Abstract In this paper a basic structural problem in Generalized Semi-Infinite Programming is solved. In fact, under natural and generic assumptions we show that at any (local) min...
Harald Günzel, Hubertus Th. Jongen, Oliver St...
PR
2007
88views more  PR 2007»
13 years 9 months ago
Robust kernel Isomap
Isomap is one of widely-used low-dimensional embedding methods, where geodesic distances on a weighted graph are incorporated with the classical scaling (metric multidimensional s...
Heeyoul Choi, Seungjin Choi
SADM
2010
173views more  SADM 2010»
13 years 4 months ago
Data reduction in classification: A simulated annealing based projection method
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
Tian Siva Tian, Rand R. Wilcox, Gareth M. James
ICIC
2009
Springer
14 years 2 months ago
Dimension Reduction Using Semi-Supervised Locally Linear Embedding for Plant Leaf Classification
Plant has plenty use in foodstuff, medicine and industry, and is also vitally important for environmental protection. So, it is important and urgent to recognize and classify plant...
Shanwen Zhang, Kwok-Wing Chau
SDM
2009
SIAM
205views Data Mining» more  SDM 2009»
14 years 7 months ago
Identifying Information-Rich Subspace Trends in High-Dimensional Data.
Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
Chandan K. Reddy, Snehal Pokharkar