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quant-ph2026
A Quantum-Inspired Dequantization Method for Diagonally Weighted Matrix Functions: Application to Learning with Optimized Random Features
Natsuto Isogai, Mio Murao, Hayata Yamasaki
Quantum-inspired classical algorithms have dequantized several quantum machine learning routines by replacing quantum linear-algebra subroutines with classical counterparts. Howeve…
quant-ph2026
Winning Lottery Tickets in Neural Networks via a Quantum-Inspired Classical Algorithm
Natsuto Isogai, Hayata Yamasaki, Sho Sonoda +1
Quantum machine learning (QML) aims to accelerate machine learning tasks by exploiting quantum computation. Previous work studied a QML algorithm for selecting sparse subnetworks f…