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Comment on 'Supervised quantum machine learning models are kernel methods'
arXiv
Authors: Rajiv Krishnakumar
Year
2026
Paper ID
76005
Status
Preprint
Abstract Read
~2 min
Abstract Words
86
Citations
N/A
Abstract
We identify a few small errors in the proof of Theorem 1 in M. Schuld, 'Supervised quantum machine learning models are kernel methods' (arXiv:2101.11020v2), Appendix A. These do not affect the validity of the theorem, but do matter if one wants to use the appendix to explicitly compute the Fourier coefficients of a quantum kernel. We give the corrected derivation, and additionally show that the paper's worked cosine-kernel example contains a second, unrelated error that happens to cancel the first, thereby coincidentally yielding the correct result.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2026 reference point for readers tracking recent quantum research.
- We identify a few small errors in the proof of Theorem 1 in M.
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