TY - GEN
T1 - Randomized ULV decomposition for approximating low-rank matrices
AU - Kaloorazi, Maboud F.
AU - Chen, Jie
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - In this paper, we present a low-rank matrix approximation algorithm called Randomized Rank-k ULV (RR-ULV) decomposition. Fundamental in our work is the exploitation of the randomized sampling paradigm, which provides an efficient strategy in order to construct an approximation of a large input matrix. Our proposed RR-ULV is computationally efficient, robust, highly accurate, and can also harness modern computational platforms. We apply RR-ULV to randomly generated data and real world data: We consider reconstructing a low-rank image, and further solving the robust principal component analysis task to validate its efficacy and efficiency. Our experimental results demonstrate that RR-ULV outperforms the existing methods.
AB - In this paper, we present a low-rank matrix approximation algorithm called Randomized Rank-k ULV (RR-ULV) decomposition. Fundamental in our work is the exploitation of the randomized sampling paradigm, which provides an efficient strategy in order to construct an approximation of a large input matrix. Our proposed RR-ULV is computationally efficient, robust, highly accurate, and can also harness modern computational platforms. We apply RR-ULV to randomly generated data and real world data: We consider reconstructing a low-rank image, and further solving the robust principal component analysis task to validate its efficacy and efficiency. Our experimental results demonstrate that RR-ULV outperforms the existing methods.
KW - Low-rank image recovery
KW - Low-rank-plus-sparse matrix decomposition
KW - Matrix factorization
KW - Randomized methods
UR - http://www.scopus.com/inward/record.url?scp=85078918700&partnerID=8YFLogxK
U2 - 10.1109/ICSPCC46631.2019.8960878
DO - 10.1109/ICSPCC46631.2019.8960878
M3 - 会议稿件
AN - SCOPUS:85078918700
T3 - 2019 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2019
BT - 2019 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2019
Y2 - 20 September 2019 through 22 September 2019
ER -