Homogeneous Structured Element Pursuit

Finding structured elements from a geometric object, with emphasis on objects containing the origin and hence associated scale ambiguity. (Update: Jan 25 2020)

[S] indicates my contribution.

Finding Sparse Vectors in Linear Subspaces

• Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications (2020)
• Dual Principal Component Pursuit: Probability Analysis and Efficient Algorithms (2018)
• Speeding up sum-of-squares for tensor decomposition and planted sparse vectors (2015)
• Dual Principal Component Pursuit (2015)
• Complete Dictionary Recovery over the Sphere (2015)
• Finding a sparse vector in a subspace: Linear sparsity using alternating directions ([S], 2014)
• Exact Recovery of Sparsely-Used Dictionaries (2012)
• Blind Source Separation by Sparse Decomposition in a Signal Dictionary (2001)

Finding Low-rank Matrices in Matrix Subspaces

• Finding a low-rank basis in a matrix subspace (2015)
• Rank-one solutions for homogeneous linear matrix equations over the positive semidefinite cone (2013)
• A simple prior-free method for non-rigid structure-from-motion factorization (2012)

Finding Sparse Elements in Tensor Subspaces

• When are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity (2013)

Disclaimer - This page is meant to serve a hub for references on this problem, and does not represent in any way personal endorsement of papers listed here. So I do not hold any responsibility for quality and technical correctness of each paper listed here. The reader is advised to use this resource with discretion.

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