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ICIP
2006
IEEE
16 years 2 months ago
Wavelet Principal Component Analysis and its Application to Hyperspectral Images
We investigate reducing the dimensionality of image sets by using principal component analysis on wavelet coefficients to maximize edge energy in the reduced dimension images. Lar...
Maya R. Gupta, Nathaniel P. Jacobson
96
Voted
IJCV
2008
155views more  IJCV 2008»
15 years 23 days ago
Fast Transformation-Invariant Component Analysis
For software and more illustrations: http://www.psi.utoronto.ca/anitha/fastTCA.htm Dimensionality reduction techniques such as principal component analysis and factor analysis are...
Anitha Kannan, Nebojsa Jojic, Brendan J. Frey
JMLR
2010
144views more  JMLR 2010»
14 years 7 months ago
Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
Alexander Ilin, Tapani Raiko
ERSHOV
1999
Springer
15 years 5 months ago
Binding-Time Analysis in Partial Evaluation: One Size Does Not Fit All
Abstract. Existing partial evaluators usually fix the strategy for binding-time analysis. But a single strategy cannot fulfill all goals without leading to compromises regarding ...
Niels H. Christensen, Robert Glück, Sø...
121
Voted
WCET
2003
15 years 2 months ago
Fully Automatic, Parametric Worst-Case Execution Time Analysis
Worst-Case Execution Time (WCET) analysis means to compute a safe upper bound to the execution time of a piece of code. Parametric WCET analysis yields symbolic upper bounds: expr...
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