Imagen de Portada

Distributed and Secure Kernel-Based Quantum Machine Learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Swaminathan, Arjhun, Akgün, Mete
Formato:	Preprint
Publicado:	2024
Materias:	Quantum Physics Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Empirical Evidence for Simply Connected Decision Regions in Image Classifiers
por: Swaminathan, Arjhun, et al.
Publicado: (2026)

Accelerating Targeted Hard-Label Adversarial Attacks in Low-Query Black-Box Settings
por: Swaminathan, Arjhun, et al.
Publicado: (2025)

Private, Efficient and Scalable Kernel Learning for Medical Image Analysis
por: Hannemann, Anika, et al.
Publicado: (2024)

A Privacy-Preserving Federated Learning Approach for Kernel methods
por: Hannemann, Anika, et al.
Publicado: (2023)

Identification and Mitigating Bias in Quantum Machine Learning
por: Swaminathan, Nandhini, et al.
Publicado: (2024)

Quantum Machine Learning: Quantum Kernel Methods
por: Naguleswaran, Sanjeev
Publicado: (2024)

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

CECILIA: Comprehensive Secure Machine Learning Framework
por: Ünal, Ali Burak, et al.
Publicado: (2022)

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

Quantum Kernel Machine Learning for Autonomous Materials Science
por: Adams, Felix, et al.
Publicado: (2026)

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

Quantum Machine Learning: Performance and Security Implications in Real-World Applications
por: Luo, Zhengping Jay, et al.
Publicado: (2024)

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

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

Security Concerns in Quantum Machine Learning as a Service
por: Kundu, Satwik, et al.
Publicado: (2024)

Quantum Generator Kernels
por: Altmann, Philipp, et al.
Publicado: (2026)

Adversarial Robustness in Distributed Quantum Machine Learning
por: Kananian, Pouya, et al.
Publicado: (2025)

Distribution-Guided and Constrained Quantum Machine Unlearning
por: Malik, Nausherwan, et al.
Publicado: (2026)

Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention
por: Evans, Ethan N., et al.
Publicado: (2024)

Benign Overfitting with Quantum Kernels
por: Tomasi, Joachim, et al.
Publicado: (2025)

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

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

Quantum Dynamics of Machine Learning
por: Wang, Peng, et al.
Publicado: (2024)

QUACK: Quantum Aligned Centroid Kernel
por: Tscharke, Kilian, et al.
Publicado: (2024)

A Resource Efficient Quantum Kernel
por: Singh, Utkarsh, et al.
Publicado: (2025)

Support Vector Machine Kernels as Quantum Propagators
por: Kuo, Nan-Hong, et al.
Publicado: (2025)

Multiple Embeddings for Quantum Machine Learning
por: Han, Siyu, et al.
Publicado: (2025)

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

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

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

Entangled Threats: A Unified Kill Chain Model for Quantum Machine Learning Security
por: Debus, Pascal, et al.
Publicado: (2025)

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

Quantum Circuit-Based Learning Models: Bridging Quantum Computing and Machine Learning
por: Fan, Fan, et al.
Publicado: (2026)

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

Entangling Machine Learning with Quantum Tensor Networks
por: van der Poel, Constantijn, et al.
Publicado: (2024)

Prospects of Privacy Advantage in Quantum Machine Learning
por: Heredge, Jamie, et al.
Publicado: (2024)

Understanding Generalization in Quantum Machine Learning with Margins
por: Hur, Tak, et al.
Publicado: (2024)

Machine Learning for Practical Quantum Error Mitigation
por: Liao, Haoran, et al.
Publicado: (2023)

Limitations of Quantum Advantage in Unsupervised Machine Learning
por: Patel, Apoorva D.
Publicado: (2025)

Exploring Quantum Machine Learning for Weather Forecasting
por: da Silva, Maria Heloísa F., et al.
Publicado: (2025)