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03/02/2023
A Field-Theoretic Approach to Unlabeled Sensing
We study the recent problem of unlabeled sensing from the information sc...
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07/22/2022
Ladder Matrix Recovery from Permutations
We give unique recovery guarantees for matrices of bounded rank that hav...
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03/28/2022
ARCS: Accurate Rotation and Correspondence Search
This paper is about the old Wahba problem in its more general form, whic...
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10/06/2021
Boosting RANSAC via Dual Principal Component Pursuit
In this paper, we revisit the problem of local optimization in RANSAC. O...
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01/23/2021
Unlabeled Principal Component Analysis
We consider the problem of principal component analysis from a data matr...
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06/09/2020
Homomorphic Sensing of Subspace Arrangements
Homomorphic sensing is a recent algebraic-geometric framework that studi...
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04/26/2020
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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03/17/2020
Linear Regression without Correspondences via Concave Minimization
Linear regression without correspondences concerns the recovery of a sig...
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02/12/2020
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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01/20/2020
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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01/23/2019
Homomorphic Sensing
A recent line of research termed unlabeled sensing and shuffled linear r...
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12/24/2018
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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12/05/2018
Eigenspace conditions for homomorphic sensing
Given two endomorphisms τ_1,τ_2 of C^m with m > 2n and a general n-dimen...
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10/12/2018
An Algebraic-Geometric Approach to Shuffled Linear Regression
Shuffled linear regression is the problem of performing a linear regress...
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01/01/2018
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
Sparse Subspace Clustering (SSC) is a popular unsupervised machine learn...
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06/06/2017
Hyperplane Clustering Via Dual Principal Component Pursuit
We extend the theoretical analysis of a recently proposed single subspac...
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10/15/2015
Filtrated Spectral Algebraic Subspace Clustering
Algebraic Subspace Clustering (ASC) is a simple and elegant method based...
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10/15/2015
Dual Principal Component Pursuit
We consider the problem of outlier rejection in single subspace learning...
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06/20/2015
