29 citations · 48 across the 7 of their papers we have counts for
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quant-ph2022★ 3 cited
Boosting Method for Automated Feature Space Discovery in Supervised Quantum Machine Learning Models
Vladimir Rastunkov, Jae-Eun Park, Abhijit Mitra +5
Quantum Support Vector Machines (QSVM) have become an important tool in research and applications of quantum kernel methods. In this work we propose a boosting approach for buildin…
quant-ph2020★ 29 cited
Practical application improvement to Quantum SVM: theory to practice
Jae-Eun Park, Brian Quanz, Steve Wood +2
Quantum machine learning (QML) has emerged as an important area for Quantum applications, although useful QML applications would require many qubits. Therefore our paper is aimed a…