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Preprint Aug 2026

Toward Quantum Advantage in Learning Parities with Structured Noise via Lower Bound Optimization of the Condition Number

This work proposes a novel reduction method for Macaulay linear systems and derives a condition number lower bound incorporating a scaling factor, demonstrating that the optimized condition number translates directly into a reduction in circuit width, depth, and gate count.

Yu-Shen Han, Xue-Lian Li, Juntao Gao et al. · 0 citations

#machine learning Preprint Sep 2026

Semi-Tensor Product-Based Multi-Term Randomized T-SVD and Its Visual Applications

Tensor singular value decomposition (T-SVD), which is built upon the tensor-tensor product (t-product), has emerged as a powerful tool for processing high-dimensional visual data such as color images and videos. However, the standard t-product imposes strict dimensional compatibility constraints. Although extensions ba...

Xing-Chen Xiao, Feng Zhang, Wen-Jin Qin et al. · 0 citations