The authors introduce a q-Hermite I polynomial SVM kernel, prove it is a valid Mercer kernel, and show it matches Gegenbauer accuracy with lower training time, but the no-scaling claim is weakened by a clipped weight.
Quantum support vector machine for classification task: A review
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Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning
The authors introduce a q-Hermite I polynomial SVM kernel, prove it is a valid Mercer kernel, and show it matches Gegenbauer accuracy with lower training time, but the no-scaling claim is weakened by a clipped weight.