Quantum Kernel Methods: Convergence Theory, Separation Bounds and Applications to Marketing Analytics

Laura Sáez-Ortuño, Santiago Forgas-Coll, Massimiliano Ferrara

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DOI: 10.21203/rs.3.rs-7842283/v1
Published: 2025-10-21
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Publisher: Springer Science and Business Media LLC
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Cite this work

BibTeX

@article{allodium:10.21203/rs.3.rs-7842283/v1,
  title = {Quantum Kernel Methods: Convergence Theory, Separation Bounds and Applications to Marketing Analytics},
  author = {Laura Sáez-Ortuño and Santiago Forgas-Coll and Massimiliano Ferrara},
  year = {2025},
  doi = {10.21203/rs.3.rs-7842283/v1},
  url = {https://doi.org/10.21203/rs.3.rs-7842283/v1}
}

RIS

TY  - JOUR
TI  - Quantum Kernel Methods: Convergence Theory, Separation Bounds and Applications to Marketing Analytics
AU  - Laura Sáez-Ortuño
AU  - Santiago Forgas-Coll
AU  - Massimiliano Ferrara
PY  - 2025
DO  - 10.21203/rs.3.rs-7842283/v1
UR  - https://doi.org/10.21203/rs.3.rs-7842283/v1
ER  -

APA

Sáez-Ortuño, L., Forgas-Coll, S., & Ferrara, M. (2025). Quantum Kernel Methods: Convergence Theory, Separation Bounds and Applications to Marketing Analytics. https://doi.org/10.21203/rs.3.rs-7842283/v1

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crossref · retrieved 2026-09-25T10:47:59.034Z