141 citations · 200 across the 8 of their papers we have counts for
8 papers
Performance Guarantees for ReProCS -- Correlated Low-Rank Matrix Entries Case
Jinchun Zhan, Namrata Vaswani, Chenlu Qiu
Online or recursive robust PCA can be posed as a problem of recovering a sparse vector, , and a dense vector, , which lies in a slowly changing low-dimensional subspace,…
Recursive Robust PCA or Recursive Sparse Recovery in Large but Structured Noise (parts 1 and 2 combined)
Chenlu Qiu, Namrata Vaswani, Brian Lois +1
This work studies the recursive robust principal components analysis (PCA) problem. If the outlier is the signal-of-interest, this problem can be interpreted as one of recursively…
An Online Algorithm for Separating Sparse and Low-dimensional Signal Sequences from their Sum
Han Guo, Chenlu Qiu, Namrata Vaswani
This paper designs and evaluates a practical algorithm, called practical recursive projected compressive sensing (Prac-ReProCS), for recovering a time sequence of sparse vectors $S…
Recursive Sparse Recovery in Large but Structured Noise - Part 2
Chenlu Qiu, Namrata Vaswani
We study the problem of recursively recovering a time sequence of sparse vectors, St, from measurements Mt := St + Lt that are corrupted by structured noise Lt which is dense and c…
Recursive Robust PCA or Recursive Sparse Recovery in Large but Structured Noise
Chenlu Qiu, Namrata Vaswani, Brian Lois +1
This work studies the recursive robust principal components' analysis(PCA) problem. Here, "robust" refers to robustness to both independent and correlated sparse outliers. If the o…
ReProCS: A Missing Link between Recursive Robust PCA and Recursive Sparse Recovery in Large but Correlated Noise
Chenlu Qiu, Namrata Vaswani
This work studies the recursive robust principal components' analysis (PCA) problem. Here, "robust" refers to robustness to both independent and correlated sparse outliers, althoug…