GBQC reduces quantum kernel evaluations by ~80% through granular-ball compression while improving clustering accuracy on complex, non-convex data via quantum feature mapping—enabling practical quantum machine learning under NISQ resource constraints.

#QuantumClustering #QuantumML #Research

EQC achieves 79.3% clustering accuracy while reducing membership inference attack success to 38.3%—demonstrating that parameter-efficient quantum clustering with differential privacy can improve both privacy and accuracy simultaneously.

#QuantumClustering #DifferentialPrivacy #Research

Quantum feature maps enable k-means with 88.6% Iris & 91% breast cancer accuracy—surpassing classical baselines. Using quantum kernels instead of Euclidean distance captures richer similarity landscapes in NISQ-era systems.

#QuantumML #QuantumClustering #NISQ