June 11, 2024, 4:46 a.m. | Zhen Qin, Zhihui Zhu

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.06002v1 Announce Type: new
Abstract: Recently, a tensor-on-tensor (ToT) regression model has been proposed to generalize tensor recovery, encompassing scenarios like scalar-on-tensor regression and tensor-on-vector regression. However, the exponential growth in tensor complexity poses challenges for storage and computation in ToT regression. To overcome this hurdle, tensor decompositions have been introduced, with the tensor train (TT)-based ToT model proving efficient in practice due to reduced memory requirements, enhanced computational efficiency, and decreased sampling complexity. Despite these practical benefits, a disparity …

abstract arxiv challenges complexity computation computational cs.lg eess.sp growth however math.oc recovery regression statistical storage tensor train type vector

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