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Principal component analysis

Known as: Principle components analysis, Principle Component Analysis, Probabilistic principal component analysis 
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2008
2008
Computer vision and image recognition research have a great interest in dimensionality reduction techniques. Generally these… 
2008
2007
2007
Abstract : Geometric harmonics provides a framework for taking data in high-dimensional measurement spaces and embedding them in… 
2006
2006
Stochastic dynamic programming models are attractive for multireservoir control problems because they allow non‐linear features… 
2005
2005
A burn-in reduction screen is presented based on a subset of measurements from the wafer sort data. The subset of wafer sort data… 
Highly Cited
1999
Highly Cited
1999
We present a face detection algorithm for color images with complex background. We include color information into a face… 
1998
1998
Research has been initiated to determine a set of six basis colorants which are the best representation of artwork such as… 
1991
1991
The scheduling problems in flexible manufacturing systems deal with (1) tool allocation (2)parts scheduling (3) pallets… 
Highly Cited
1986
Highly Cited
1986
The concept of fast KL transform coding introduced earlier [7], [8] for first-order Markov processes and certain random fields… 
Highly Cited
1981
Highly Cited
1981
A class of stable algorithms for adapting infinite impulse response (IIR) digital filters based on the concepts of nonlinear…