arXiv Machine Learning July 23, 2026 By Kilian Tscharke, Pascal Debus

A Multiclass Quantum Aligned Centroid Kernel

Read the original on arXiv Machine Learning →

arXiv:2607. 19782v1 Announce Type: cross Abstract: Kernel methods are powerful tools in machine learning but commonly used full-Gram kernels face three key limitations: (1) quadratic scaling with training set size; (2) the use of fixed, non-trainable kernels; and (3) the absence of an intrinsic formulation for multiclass classification.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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