
Homomorphic Sensing of Subspace Arrangements
Homomorphic sensing is a recent algebraicgeometric framework that studi...
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An exposition to the finiteness of fibers in matrix completion via Plücker coordinates
Matrix completion is a popular paradigm in machine learning and data sci...
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Linear Regression without Correspondences via Concave Minimization
Linear regression without correspondences concerns the recovery of a sig...
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Finiteness of fibers in matrix completion via Plücker coordinates
Let Ω⊆{1,...,m}×{1,...,n}. We consider fibers of coordinate projections ...
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Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications
The problem of finding the sparsest vector (direction) in a low dimensio...
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Homomorphic Sensing
A recent line of research termed unlabeled sensing and shuffled linear r...
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Dual Principal Component Pursuit: Probability Analysis and Efficient Algorithms
Recent methods for learning a linear subspace from data corrupted by out...
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Eigenspace conditions for homomorphic sensing
Given two endomorphisms τ_1,τ_2 of C^m with m > 2n and a general ndimen...
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An AlgebraicGeometric Approach to Shuffled Linear Regression
Shuffled linear regression is the problem of performing a linear regress...
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Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
Sparse Subspace Clustering (SSC) is a popular unsupervised machine learn...
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Hyperplane Clustering Via Dual Principal Component Pursuit
We extend the theoretical analysis of a recently proposed single subspac...
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Filtrated Spectral Algebraic Subspace Clustering
Algebraic Subspace Clustering (ASC) is a simple and elegant method based...
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Dual Principal Component Pursuit
We consider the problem of outlier rejection in single subspace learning...
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Filtrated Algebraic Subspace Clustering
Subspace clustering is the problem of clustering data that lie close to ...
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