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Xiao-Yu Li

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Open access Aug 2026

STOD: Sparse Tensor Train Optimization via Orthogonal Decomposition for High-Dimensional Learning

This paper proposes a novel Tensor Train (TT)-based tensor-on-tensor regression optimization framework for variable selection based on mode-1 hyperslice sparsity, and designs an alternating iterative algorithm equipped with a preconditioned metric to efficiently solve the proposed model.

Xiao-Yu Li, Zi-Yan Luo · 0 citations

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