Results 41 to 50 of about 9,171,861 (296)

Structured Low-rank Approximation as a Rational Function Minimization [PDF]

, 2012
Many problems of system identification, model reduction and signal processing can be posed and solved as a structured low-rank approximation problem (SLRA).
Markovsky, Ivan, Usevich, Konstantin
core   +1 more source

A PTAS for ℓ_p-Low Rank Approximation [PDF]

, 2019
Accepted at SODA'19, 65 ...
Ban, F., Bhattiprolu, V., Bringmann, K. ; https://orcid.org/0000-0003-1356-5177, Kolev, P., Lee, E., Woodruff, D.   +5 more
openaire   +6 more sources

Multimodal Trajectory Prediction with Low-Rank Approximation and Pyramid Features [PDF]

Jisuanji kexue yu tansuo
Capturing high-dimensional social interactions and trend features is essential for accurately predicting the feasible future behaviors of agents. To address this complexity, previous research has reduced the dimensionality of input variables through ...
LIU Guihong, ZHAI Zhuoyu, ZHANG Xiaoyan, LENG Qiangkui
doaj   +1 more source

Adaptive System Identification via Low-Rank Tensor Decomposition

IEEE Access, 2021
Tensor-based estimation has been of particular interest of the scientific community for several years now. While showing promising results on system estimation and other tasks, one big downside is the tremendous amount of computational power and memory ...
Christina Auer, Oliver Ploder, Thomas Paireder, Peter Kovacs, Oliver Lang, Mario Huemer   +5 more
doaj   +1 more source

Dynamic Magnetic Resonance Imaging via Nonconvex Low-Rank Matrix Approximation

IEEE Access, 2017
Reconstruction of highly accelerated dynamic magnetic resonance imaging (MRI) is of crucial importance for the medical diagnosis. The application of general robust principal component analysis (RPCA) to MRI can increase imaging speed and efficiency ...
Fei Xu, Jingqi Han, Yongli Wang, Ming Chen, Yongyong Chen, Guoping He, Yunhong Hu   +6 more
doaj   +1 more source

Low Rank Approximation of Multidimensional Data [PDF]

, 2019
IV Research and Transfer Plan of the University of ...
Azaïez, Mejdi, Lestandi, Lucas, Chacón Rebollo, Tomás   +2 more
openaire   +2 more sources

Low Phase-Rank Approximation

, 2022
In this paper, we propose and solve low phase-rank approximation problems, which serve as a counterpart to the well-known low-rank approximation problem and the Schmidt-Mirsky theorem.
Zhao, D., Qiu, Li, Khong, Sei Zhen, Qiu, L., Ringh, Axel, Khong, S. Z., Zhao, Di,, Khong, Sei Zhen,, Zhao, Di, Ringh, Axel,, Qiu, Li,   +10 more
core   +1 more source

Low-rank approximation for underwater drone localization

ICT Express
We herein propose a low-approximated least-squares method for underwater drone localization that does not require depth information. On the basis of error analysis, we propose a rule to deploy a set of surface drones that minimizes the impact of ...
Goo-Jung Park, Jung-Hoon Noh, Seong-Jun Oh   +2 more
doaj   +1 more source

Robust Low-Rank Graph Multi-View Clustering via Cauchy Norm Minimization

Mathematics, 2023
Graph-based multi-view clustering methods aim to explore the partition patterns by utilizing a similarity graph. However, many existing methods construct a consensus similarity graph based on the original multi-view space, which may result in the lack of
Xinyu Pu, Baicheng Pan, Hangjun Che
doaj   +1 more source

Consistent Low-Rank Approximation

CoRR
ICLR ...
David P. Woodruff, Samson Zhou
openaire   +3 more sources