4 papers
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…