May 15, 2024, 4:46 a.m. | Katherine Henneberger, Jing Qin

cs.CV updates on arXiv.org arxiv.org

arXiv:2405.08275v1 Announce Type: cross
Abstract: Tensors serve as a crucial tool in the representation and analysis of complex, multi-dimensional data. As data volumes continue to expand, there is an increasing demand for developing optimization algorithms that can directly operate on tensors to deliver fast and effective computations. Many problems in real-world applications can be formulated as the task of recovering high-order tensors characterized by sparse and/or low-rank structures. In this work, we propose novel Kaczmarz algorithms with a power of …

abstract algorithms analysis and analysis arxiv cs.cv cs.na data demand expand math.na math.oc norm optimization power recovery representation serve tensor tool type

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