4 citations · 8 across the 2 of their papers we have counts for
3 papers · 1 filter
Accelerating Grover Adaptive Search: Qubit and Gate Count Reduction Strategies with Higher-Order Formulations
Yuki Sano, Kosuke Mitarai, Naoki Yamamoto +1
Grover adaptive search (GAS) is a quantum exhaustive search algorithm designed to solve binary optimization problems. In this paper, we propose higher-order binary formulations tha…
Quantum Fisher kernel for mitigating the vanishing similarity issue
Yudai Suzuki, Hideaki Kawaguchi, Naoki Yamamoto
Quantum kernel method is a machine learning model exploiting quantum computers to calculate the quantum kernels (QKs) that measure the similarity between data. Despite the potentia…
Deterministic and random features for large-scale quantum kernel machine
Kouhei Nakaji, Hiroyuki Tezuka, Naoki Yamamoto
Quantum machine learning (QML) is the spearhead of quantum computer applications. In particular, quantum neural networks (QNN) are actively studied as the method that works both in…