Cover Image

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

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sáez-Ortuño, Laura, Forgas-Coll, Santiago, Ferrara, Massimiliano
Format:	Preprint
Published:	2025
Subjects:	Quantum Physics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for Deep Quantum Machine Learning
by: Incudini, Massimiliano, et al.
Published: (2022)

Quantum Machine Learning: Quantum Kernel Methods
by: Naguleswaran, Sanjeev
Published: (2024)

Spectral Phase Encoding for Quantum Kernel Methods
by: Gómez, Pablo Herrero, et al.
Published: (2026)

A Hyperparameter Study for Quantum Kernel Methods
by: Egginger, Sebastian, et al.
Published: (2023)

In Search of Quantum Advantage: Estimating the Number of Shots in Quantum Kernel Methods
by: Miroszewski, Artur, et al.
Published: (2024)

Quantum Kernel Methods under Scrutiny: A Benchmarking Study
by: Schnabel, Jan, et al.
Published: (2024)

Quantum Adversarial Learning for Kernel Methods
by: Montalbano, Giuseppe, et al.
Published: (2024)

Quantum Generator Kernels
by: Altmann, Philipp, et al.
Published: (2026)

An Analytic Theory of Quantum Imaginary Time Evolution
by: Chen, Min, et al.
Published: (2025)

Benign Overfitting with Quantum Kernels
by: Tomasi, Joachim, et al.
Published: (2025)

Enhanced Prediction of CAR T-Cell Cytotoxicity with Quantum-Kernel Methods
by: Utro, Filippo, et al.
Published: (2025)

A Resource Efficient Quantum Kernel
by: Singh, Utkarsh, et al.
Published: (2025)

QUACK: Quantum Aligned Centroid Kernel
by: Tscharke, Kilian, et al.
Published: (2024)

Entanglement Detection with Quantum-inspired Kernels and SVMs
by: Martínez-Sabiote, Ana, et al.
Published: (2025)

Position: Quantum Kernel Machines Should Move Beyond Scalar-Valued Kernels to Realize Their Potential
by: Kadri, Hachem, et al.
Published: (2025)

Quantum Policy Gradient in Reproducing Kernel Hilbert Space
by: Bossens, David M., et al.
Published: (2024)

Distributed and Secure Kernel-Based Quantum Machine Learning
by: Swaminathan, Arjhun, et al.
Published: (2024)

Modeling Quantum Autoencoder Trainable Kernel for IoT Anomaly Detection
by: Chandrasekhar, Swathi, et al.
Published: (2025)

Quantum Kernels for Parity-Structured Classification: A Hybrid Pipeline
by: Pandey, Tushar
Published: (2026)

Quantum Kernel Learning for Small Dataset Modeling in Semiconductor Fabrication: Application to Ohmic Contact
by: Wang, Zeheng, et al.
Published: (2024)

Improving Gradient Methods via Coordinate Transformations: Applications to Quantum Machine Learning
by: Bermejo, Pablo, et al.
Published: (2023)

Arbitrary Polynomial Separations in Trainable Quantum Machine Learning
by: Anschuetz, Eric R., et al.
Published: (2024)

Experimental Machine Learning with Classical and Quantum Data via NMR Quantum Kernels
by: Sabarad, Vivek, et al.
Published: (2024)

A Versatile Variational Quantum Kernel Framework for Non-Trivial Classification
by: Yuhan, Jiang, et al.
Published: (2025)

Enhancing Quantum Support Vector Machines through Variational Kernel Training
by: Innan, Nouhaila, et al.
Published: (2023)

Kernel Learning for Regression via Quantum Annealing Based Spectral Sampling
by: Hasegawa, Yasushi, et al.
Published: (2026)

QuaRK: A Quantum Reservoir Kernel for Time Series Learning
by: Aaraba, Abdallah, et al.
Published: (2026)

Geometric and Quantum Kernel Methods for Predicting Skeletal Muscle Outcomes in chronic obstructive pulmonary disease
by: Alavi, Azadeh, et al.
Published: (2026)

Quantum Interval Bound Propagation for Certified Training of Quantum Neural Networks
by: Andrews, Emma, et al.
Published: (2026)

Q2SAR: A Quantum Multiple Kernel Learning Approach for Drug Discovery
by: Giraldo, Alejandro, et al.
Published: (2025)

Enhancing Small Dataset Classification Using Projected Quantum Kernels with Convolutional Neural Networks
by: Alagiyawanna, A. M. A. S. D., et al.
Published: (2026)

Q-SINDy: Quantum-Kernel Sparse Identification of Nonlinear Dynamics with Provable Coefficient Debiasing
by: Roy, Samrendra, et al.
Published: (2026)

Quantum Theory and Application of Contextual Optimal Transport
by: Mariella, Nicola, et al.
Published: (2024)

Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits
by: Yu, Zhan, et al.
Published: (2023)

Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits
by: Du, Yuxuan, et al.
Published: (2024)

DyPP: Dynamic Parameter Prediction to Accelerate Convergence of Variational Quantum Algorithms
by: Kundu, Satwik, et al.
Published: (2023)

Theory for Equivariant Quantum Neural Networks
by: Nguyen, Quynh T., et al.
Published: (2022)

Efficient Parameter Optimisation for Quantum Kernel Alignment: A Sub-sampling Approach in Variational Training
by: Sahin, M. Emre, et al.
Published: (2024)

Empirical Quantum Advantage Analysis of Quantum Kernel in Gene Expression Data
by: Ghosh, Arpita, et al.
Published: (2024)

Evaluating the Impact of Different Quantum Kernels on the Classification Performance of Support Vector Machine Algorithm: A Medical Dataset Application
by: Akpinar, Emine, et al.
Published: (2024)