Develops a threshold-regularized Moore-Penrose pseudoinverse formulation of PGM with hybrid classical-quantum circuit implementation using block-encoding for stable discrimination in ill-conditioned and rank-deficient ensembles.
Multi-class classification based on quantum state discrimination
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
QSMOTE variants with PGM and KPGM classifiers outperform Random Forest on imbalanced Telco churn data, reaching 0.8512 accuracy and 0.8234 F1 using stereo encoding with two quantum copies.
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Robust Pretty Good Measurement via Hybrid Classical-Quantum Pseudoinverse Approximation and Circuit-Level Realization
Develops a threshold-regularized Moore-Penrose pseudoinverse formulation of PGM with hybrid classical-quantum circuit implementation using block-encoding for stable discrimination in ill-conditioned and rank-deficient ensembles.