Copertina

Hybrid Heuristic Algorithms for Adiabatic Quantum Machine Learning Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Alidaee, Bahram, Wang, Haibo, Sua, Lutfu, Liu, Wade
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Quantum Physics Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Enhancing supply chain security with automated machine learning
di: Wang, Haibo, et al.
Pubblicazione: (2024)

Renewable Energy Prediction: A Comparative Study of Deep Learning Models for Complex Dataset Analysis
di: Wang, Haibo, et al.
Pubblicazione: (2025)

Deep Learning in Renewable Energy Forecasting: A Cross-Dataset Evaluation of Temporal and Spatial Models
di: Sua, Lutfu, et al.
Pubblicazione: (2025)

Will Southeast Asia be the next global manufacturing hub? A multiway cointegration, causality, and dynamic connectedness analyses on factors influencing offshore decisions
di: Wang, Haibo, et al.
Pubblicazione: (2024)

Adiabatic Quantum Support Vector Machines
di: Date, Prasanna, et al.
Pubblicazione: (2024)

Multilevel Facility Location Optimization: A Novel Integer Programming Formulation and Approaches to Heuristic Solutions
di: Alidaee, Bahram, et al.
Pubblicazione: (2024)

Dynamic Risk in the U.S. Banking System: An Analysis of Sentiment, Policy Shocks, and Spillover Effects
di: Wang, Haibo, et al.
Pubblicazione: (2026)

A Heuristic Framework of Variable Neighborhood Descent Methods for the Large-Scale Multi-Level Facility Location Problem in Supply Chain Networks
di: Wang, Haibo, et al.
Pubblicazione: (2025)

Compilation, Optimization, Error Mitigation, and Machine Learning in Quantum Algorithms
di: Wang, Shuangbao Paul, et al.
Pubblicazione: (2025)

Enhancing Credit Risk Prediction: A Multi-stage Ensemble Pipeline
di: Wang, Haibo, et al.
Pubblicazione: (2025)

A Qubit-Efficient Hybrid Quantum Encoding Mechanism for Quantum Machine Learning
di: Cowlessur, Hevish, et al.
Pubblicazione: (2025)

Partitioned Hybrid Quantum Fourier Neural Operators for Scientific Quantum Machine Learning
di: Marcandelli, Paolo, et al.
Pubblicazione: (2025)

Quantum-Classical Machine learning by Hybrid Tensor Networks
di: Liu, Ding, et al.
Pubblicazione: (2020)

QuXAI: Explainers for Hybrid Quantum Machine Learning Models
di: Barua, Saikat, et al.
Pubblicazione: (2025)

Improving Quantum Machine Learning via Heat-Bath Algorithmic Cooling
di: Rodríguez-Briones, Nayeli A., et al.
Pubblicazione: (2025)

VQC-MLPNet: An Unconventional Hybrid Quantum-Classical Architecture for Scalable and Robust Quantum Machine Learning
di: Qi, Jun, et al.
Pubblicazione: (2025)

Quantum Dynamics of Machine Learning
di: Wang, Peng, et al.
Pubblicazione: (2024)

Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation
di: Franz, Maja, et al.
Pubblicazione: (2024)

Quantum Data Encoding and Variational Algorithms: A Framework for Hybrid Quantum Classical Machine Learning
di: Bose, Bhavna, et al.
Pubblicazione: (2025)

From Betti Numbers to Persistence Diagrams: A Hybrid Quantum Algorithm for Topological Data Analysis
di: Liu, Dong
Pubblicazione: (2025)

On the Design of Expressive and Trainable Pulse-based Quantum Machine Learning Models
di: Tao, Han-Xiao, et al.
Pubblicazione: (2025)

Cross-Problem Parameter Transfer in Quantum Approximate Optimization Algorithm: A Machine Learning Approach
di: Nguyen, Kien X., et al.
Pubblicazione: (2025)

Hybrid Quantum--Classical Machine Learning Potential with Variational Quantum Circuits
di: Willow, Soohaeng Yoo, et al.
Pubblicazione: (2025)

Q-MAML: Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms
di: Lee, Junyong, et al.
Pubblicazione: (2025)

Efficient Mutation Testing of Quantum Machine Learning Models
di: Andrews, Emma, et al.
Pubblicazione: (2026)

Benchmarking Machine Learning Models for Quantum Error Correction
di: Zhao, Yue
Pubblicazione: (2023)

Adiabatic Fine-Tuning of Neural Quantum States Enables Detection of Phase Transitions in Weight Space
di: Hernandes, Vinicius, et al.
Pubblicazione: (2025)

Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm
di: Liang, Zhiding, et al.
Pubblicazione: (2024)

Generalization of Quantum Machine Learning Models Using Quantum Fisher Information Metric
di: Haug, Tobias, et al.
Pubblicazione: (2023)

Quantum Machine Learning: Quantum Kernel Methods
di: Naguleswaran, Sanjeev
Pubblicazione: (2024)

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

Quantum Hybrid Support Vector Machines for Stress Detection in Older Adults
di: Onim, Md Saif Hassan, et al.
Pubblicazione: (2025)

You Only Measure Once: On Designing Single-Shot Quantum Machine Learning Models
di: Liu, Chen-Yu, et al.
Pubblicazione: (2025)

Quantum Machine Learning via Contrastive Training
di: Zhukas, Liudmila A., et al.
Pubblicazione: (2025)

Quantum Algorithm for Sparse Online Learning with Truncated Gradient Descent
di: Lim, Debbie, et al.
Pubblicazione: (2024)

Quantum-Informed Machine Learning for Predicting Spatiotemporal Chaos with Practical Quantum Advantage
di: Wang, Maida, et al.
Pubblicazione: (2025)

Noise Models Impacts and Mitigation Strategies in Photonic Quantum Machine Learning
di: Alagiyawanna, A. M. A. S. D., et al.
Pubblicazione: (2026)

Hybrid Classical-Quantum Transfer Learning with Noisy Quantum Circuits
di: Martín-Pérez, D., et al.
Pubblicazione: (2026)

Differentiating and Integrating ZX Diagrams with Applications to Quantum Machine Learning
di: Wang, Quanlong, et al.
Pubblicazione: (2022)

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