77 citations · 83 across the 7 of their papers we have counts for
9 papers
An Integer Programming Approach To Subspace Clustering With Missing Data
Akhilesh Soni, Jeff Linderoth, Jim Luedtke +1
In the Subspace Clustering with Missing Data (SCMD) problem, we are given a collection of n partially observed d-dimensional vectors. The data points are assumed to be concentrated…
A Perturbation Bound on the Subspace Estimator from Canonical Projections
Karan Srivastava, Daniel L. Pimentel-Alarcón
This paper derives a perturbation bound on the optimal subspace estimator obtained from a subset of its canonical projections contaminated by noise. This fundamental result has imp…
GLIMPS: A Greedy Mixed Integer Approach for Super Robust Matched Subspace Detection
Md Mahfuzur Rahman, Daniel Pimentel-Alarcon
Due to diverse nature of data acquisition and modern applications, many contemporary problems involve high dimensional datum $\x \in \R^\d$ whose entries often lie in a union of su…
Fusion Subspace Clustering: Full and Incomplete Data
Daniel L. Pimentel-Alarcón, Usman Mahmood
Modern inference and learning often hinge on identifying low-dimensional structures that approximate large scale data. Subspace clustering achieves this through a union of linear s…
Mixture Matrix Completion
Daniel L. Pimentel-Alarcón
Completing a data matrix X has become an ubiquitous problem in modern data science, with applications in recommender systems, computer vision, and networks inference, to name a few…
Tensor Methods for Nonlinear Matrix Completion
Greg Ongie, Daniel Pimentel-Alarcón, Laura Balzano +2
In the low-rank matrix completion (LRMC) problem, the low-rank assumption means that the columns (or rows) of the matrix to be completed are points on a low-dimensional linear alge…
A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion
Daniel L. Pimentel-Alarcón, Nigel Boston, Robert D. Nowak
Low-rank matrix completion (LRMC) problems arise in a wide variety of applications. Previous theory mainly provides conditions for completion under missing-at-random samplings. Thi…
Deterministic Conditions for Subspace Identifiability from Incomplete Sampling
Daniel L. Pimentel-Alarcón, Robert D. Nowak, Nigel Boston
Consider a generic -dimensional subspace of , , and suppose that we are only given projections of this subspace onto small subsets of the canonical coordinate…
To lie or not to lie in a subspace
Daniel L. Pimentel-Alarcón
Give deterministic necessary and sufficient conditions to guarantee that if a subspace fits certain partially observed data from a union of subspaces, it is because such data reall…