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Linearity-Aware Subspace Clustering
Proceedings of the AAAI Conference on Artificial Intelligence, 2022Obtaining a good similarity matrix is extremely important in subspace clustering. Current state-of-the-art methods learn the similarity matrix through self-expressive strategy. However, these methods directly adopt original samples as a set of basis to represent itself linearly. It is difficult to accurately describe the linear relation between samples
Yesong Xu +3 more
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Subspace linear inverse method
Inverse Problems, 1994The paper describes a numerical algorithm for the iterative solution of large scale linear inverse problems. From optimization point of view weighted least squares subject to parameters which are compatible with the data are used to find approximate solutions of linear inverse problems.
Oldenburg, Douglas W., Li, Yaoguo
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2021
In this chapter, we start introducing some more interesting and useful properties of matrices and linear transformations. While we begin the chapter by motivating these various properties via systems of linear equations, it is important to keep in mind that systems of linear equations are just one of the many uses of matrices.
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In this chapter, we start introducing some more interesting and useful properties of matrices and linear transformations. While we begin the chapter by motivating these various properties via systems of linear equations, it is important to keep in mind that systems of linear equations are just one of the many uses of matrices.
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Subspaces, Linear Dependence, Dimension
1983Consider a homogeneous system of linear equations in x1,...,xn such as we have studied in Chapter 5.1. What “geometric object” in ℝn is described by this system?
Thomas Banchoff, John Wermer
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Sparse subspace linear discriminant analysis
Statistics, 2018ABSTRACTWe study high dimensional multigroup classification from a sparse subspace estimation perspective, unifying the linear discriminant analysis (LDA) with other recent developments in high dim...
Yanfang Li, Jing Lei
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How Many Subspaces Force Linearity?
The American Mathematical Monthly, 2001Example 1.1. Consider the field Et of real numbers as a vector space over itself. We construct a mapping f: Et -> Et satisfying (1) but not (2). First consider Et as vector space over Q, the field of rational numbers. Let 'H be a basis for Et over Q; such a basis is sometimes called a Hamel basis.
C. J. Maxson, J. H. Meyer
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TL-submodules and TL-linear subspaces
Fuzzy Sets and Systems, 1994zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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