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20172021
most citedSubspace-Orbit Randomized Decomposition for Low-rank Matrix Approximation

49 citations · 72 across the 7 of their papers we have counts for

collaborators

7 papers

math.NA2021★ 1 cited

An Efficient Randomized QLP Algorithm for Approximating the Singular Value Decomposition

M. F. Kaloorazi, K. Liu, J. Chen +1

In this paper, we introduce a randomized QLP decomposition called Rand-QLP. Operating on a matrix , Rand-QLP gives , where and are ortho…

cs.LG2021★ 22 cited

Projection-based QLP Algorithm for Efficiently Computing Low-Rank Approximation of Matrices

Maboud F. Kaloorazi, Jie Chen

Matrices with low numerical rank are omnipresent in many signal processing and data analysis applications. The pivoted QLP (p-QLP) algorithm constructs a highly accurate approximat…

cs.DS2019

Study of Compressed Randomized UTV Decompositions for Low-Rank Matrix Approximations in Data Science

M. Kaloorazi, R. C. de Lamare

In this work, a novel rank-revealing matrix decomposition algorithm termed Compressed Randomized UTV (CoR-UTV) decomposition along with a CoR-UTV variant aided by the power method…

math.NA2018

Randomized Rank-Revealing UZV Decomposition for Low-Rank Approximation of Matrices

Maboud F. Kaloorazi, Rodrigo C. de Lamare

Low-rank matrix approximation plays an increasingly important role in signal and image processing applications. This paper presents a new rank-revealing decomposition method called…

math.NA2018

Compressed Randomized UTV Decompositions for Low-Rank Approximations and Big Data Applications

M. Kaloorazi, R. C. de Lamare

Low-rank matrix approximations play a fundamental role in numerical linear algebra and signal processing applications. This paper introduces a novel rank-revealing matrix decomposi…

math.NA2018★ 49 cited

Subspace-Orbit Randomized Decomposition for Low-rank Matrix Approximation

Maboud F. Kaloorazi, Rodrigo C. de Lamare

An efficient, accurate and reliable approximation of a matrix by one of lower rank is a fundamental task in numerical linear algebra and signal processing applications. In this pap…

cs.IT2017

Study of Anomaly Detection Based on Randomized Subspace Methods in IP Networks

M. Kaloorazi, R. C. de Lamare

In this paper we propose novel randomized subspace methods to detect anomalies in Internet Protocol networks. Given a data matrix containing information about network traffic, the…