2026 arXiv Advantage of Sample Complexity in Quantum PAC Learning Requires Inverse Access to State-Preparation Unitaries Natsuto Isogai, Satoshi Yoshida, and Mio Murao arXiv preprint arXiv:2609.38403, Sep 2026 DOI arXiv HTML arXiv A Quantum-Inspired Dequantization Method for Diagonally Weighted Matrix Functions: Application to Learning with Optimized Random Features Natsuto Isogai, Mio Murao, and Hayata Yamasaki arXiv preprint arXiv:2609.10729, Sep 2026 DOI arXiv HTML npj Quantum Inf. Advantage of Quantum Machine Learning from General Computational Advantages Hayata Yamasaki, Natsuto Isogai, and Mio Murao npj Quantum Information, Jul 2026 DOI arXiv HTML arXiv Winning Lottery Tickets in Neural Networks via a Quantum-Inspired Classical Algorithm Natsuto Isogai, Hayata Yamasaki, Sho Sonoda, and 1 more author arXiv preprint arXiv:2605.13979, May 2026 DOI arXiv HTML