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Oblique Projection Matching Pursuit
Mobile Networks and Applications, 2016Recent theory of compressed sensing (CS) tells us that sparse signals can be reconstructed from a small number of random samples. In reconstruction of sparse signals, greedy algorithms, such as the orthogonal matching pursuit (OMP), have been shown to be computationally efficient.
Jian Wang 0016 +3 more
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WIREs Computational Statistics, 2009
AbstractProjection pursuit is a technique for finding highly informative low‐dimensional projections of multivariate data for visual inspection by an analyst. When data of dimension m are reduced to dimension p (where typically p = 2 is the most useful for viewing by scatter plots), the method consists of defining a measure of information content in ...
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AbstractProjection pursuit is a technique for finding highly informative low‐dimensional projections of multivariate data for visual inspection by an analyst. When data of dimension m are reduced to dimension p (where typically p = 2 is the most useful for viewing by scatter plots), the method consists of defining a measure of information content in ...
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Automatic Induction of Projection Pursuit Indices
IEEE Transactions on Neural Networks, 2010Projection techniques are frequently used as the principal means for the implementation of feature extraction and dimensionality reduction for machine learning applications. A well established and broad class of such projection techniques is the projection pursuit (PP).
Eduardo Rodríguez-Martínez +3 more
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Exploratory Projection Pursuit
1995“Projection Pursuit” (PP) stands for a class of exploratory projection techniques. This class contains methods designed for analyzing high dimensional data using low-dimensional projections. The main idea is to describe “interesting” projections by maximizing an objective function or projection pursuit index.
Sigbert Klinke, Jörg Polzehl
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IJCNN-91-Seattle International Joint Conference on Neural Networks, 2002
A learning model based on a nonparametric statistical technique, projection pursuit regression, is studied. Projection pursuit is a nonparametric statistical technique to find interesting low-dimensional projections of high-dimensional data sets. Projection pursuit regression approximates a function of q variables by a sum of nonlinear functions of ...
Y. Zhao, C.G. Atkeson
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A learning model based on a nonparametric statistical technique, projection pursuit regression, is studied. Projection pursuit is a nonparametric statistical technique to find interesting low-dimensional projections of high-dimensional data sets. Projection pursuit regression approximates a function of q variables by a sum of nonlinear functions of ...
Y. Zhao, C.G. Atkeson
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Neural Computation, 1993
We present a novel classification and regression method that combines exploratory projection pursuit (unsupervised training) with projection pursuit regression (supervised training), to yield a new family of cost/complexity penalty terms. Some improved generalization properties are demonstrated on real-world problems.
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We present a novel classification and regression method that combines exploratory projection pursuit (unsupervised training) with projection pursuit regression (supervised training), to yield a new family of cost/complexity penalty terms. Some improved generalization properties are demonstrated on real-world problems.
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Fuzzy Sets and Systems, 1988
Two objections to the ``classical'' approach in projection pursuit have inspired the authors to translate the classical projection pursuit technology for a fuzzy-reasoning approach. These are: (i) The classical approach takes into account all axes (all components of data) with the same weights not assuming different importance, precision etc., (ii) the
Bandemer, Hans, Näther, Wolfgang
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Two objections to the ``classical'' approach in projection pursuit have inspired the authors to translate the classical projection pursuit technology for a fuzzy-reasoning approach. These are: (i) The classical approach takes into account all axes (all components of data) with the same weights not assuming different importance, precision etc., (ii) the
Bandemer, Hans, Näther, Wolfgang
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Projection pursuit by involution
Communications in Statistics - Simulation and Computation, 1997A novel projection pursuit method based on projecting the data onto itself is proposed. Using a number of real datasets it is shown how to obtain interesting one and two-dimensional projections using only O(n) evaluations of a one-dimensional projection index.
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2017
Preface. Part 1. Personal Project Pursuit: Theoretical and Methodological Foundations. B.R. Little, Prompt and Circumstance: The Generative Contexts of Personal Projects Analysis. B.R. Little, T.L. Gee, The Methodology of Personal Projects Analysis: Four Modules and a Funnel. Part 2. Basic Processes of Project Pursuit: Internal Regulatory Functions.
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Preface. Part 1. Personal Project Pursuit: Theoretical and Methodological Foundations. B.R. Little, Prompt and Circumstance: The Generative Contexts of Personal Projects Analysis. B.R. Little, T.L. Gee, The Methodology of Personal Projects Analysis: Four Modules and a Funnel. Part 2. Basic Processes of Project Pursuit: Internal Regulatory Functions.
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