Imagen de Portada

Quantum Policy Gradient in Reproducing Kernel Hilbert Space

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Bossens, David M., Bharti, Kishor, Thompson, Jayne
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

On Quantum Natural Policy Gradients
por: Sequeira, André, et al.
Publicado: (2024)

Policy Newton Algorithm in Reproducing Kernel Hilbert Space
por: Zhang, Yixian, et al.
Publicado: (2025)

Robust Lagrangian and Adversarial Policy Gradient for Robust Constrained Markov Decision Processes
por: Bossens, David M.
Publicado: (2023)

Quantum-Assisted Hilbert-Space Gaussian Process Regression
por: Farooq, Ahmad, et al.
Publicado: (2024)

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

Reproducing Kernel Hilbert Space Approach to Non-Markovian Quantum Stochastic Models
por: Gough, John E., et al.
Publicado: (2024)

Quantum Maximum Likelihood Prediction via Hilbert Space Embeddings
por: Sreekumar, Sreejith, et al.
Publicado: (2026)

QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning
por: Chittoor, Hari Hara Suthan, et al.
Publicado: (2024)

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

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

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

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

A quantum tug of war between randomness and symmetries on homogeneous spaces
por: Arvind, Rahul, et al.
Publicado: (2023)

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

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

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)

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

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach
por: Xu, Yang, et al.
Publicado: (2025)

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

On the Convergence of Irregular Sampling in Reproducing Kernel Hilbert Spaces
por: Iske, Armin
Publicado: (2025)

Kernel VICReg for Self-Supervised Learning in Reproducing Kernel Hilbert Space
por: Sepanj, M. Hadi, et al.
Publicado: (2025)

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

Quantum Shadow Gradient Descent for Variational Quantum Algorithms
por: Heidari, Mohsen, et al.
Publicado: (2023)

Learning of Hamiltonian Dynamics with Reproducing Kernel Hilbert Spaces
por: Smith, Torbjørn, et al.
Publicado: (2023)

QPPG: Quantum-Preconditioned Policy Gradient for Link Adaptation in Rayleigh Fading Channels
por: Giwa, Oluwaseyi, et al.
Publicado: (2025)

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

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

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

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

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

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

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

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

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

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

On Quasi-Localized Dual Pairs in Reproducing Kernel Hilbert Spaces
por: Harbrecht, Helmut, et al.
Publicado: (2024)

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

Quantum Kernel Methods: Convergence Theory, Separation Bounds and Applications to Marketing Analytics
por: Sáez-Ortuño, Laura, et al.
Publicado: (2025)

Strategic Code: A Unified Spatio-Temporal Framework for Quantum Error-Correction
por: Tanggara, Andrew, et al.
Publicado: (2024)