Cover Image

Quantum Shadow Gradient Descent for Variational Quantum Algorithms

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Heidari, Mohsen, Naved, Mobasshir A, Honjani, Zahra, Xie, Wenbo, Grama, Arjun Jacob, Szpankowski, Wojciech
Format:	Preprint
Published:	2023
Subjects:	Quantum Physics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

New Bounds on Quantum Sample Complexity of Measurement Classes
by: Heidari, Mohsen, et al.
Published: (2024)

Efficient Gradient Estimation for Parameterized Quantum Systems with Lie Algebraic Symmetries
by: Heidari, Mohsen, et al.
Published: (2024)

Improved Classical Shadow Tomography Using Quantum Computation
by: Honjani, Zahra, et al.
Published: (2025)

Accelerating Feedback-based Algorithms for Quantum Optimization Using Gradient Descent
by: Mozakka, Masih, et al.
Published: (2026)

Query Learning Nearly Pauli Sparse Unitaries in Diamond Distance
by: Honjani, Zahra, et al.
Published: (2026)

Quantum Natural Stochastic Pairwise Coordinate Descent
by: Sohail, Mohammad Aamir, et al.
Published: (2024)

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

Robust Online Classification: From Estimation to Denoising
by: Wu, Changlong, et al.
Published: (2023)

No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
by: Wu, Changlong, et al.
Published: (2024)

Superpositional Gradient Descent: Harnessing Quantum Principles for Model Training
by: Pamuk, Ahmet Erdem, et al.
Published: (2025)

Fast Quantum Process Tomography via Riemannian Gradient Descent
by: Volya, Daniel, et al.
Published: (2024)

Quantum Optimization via Gradient-Based Hamiltonian Descent
by: Leng, Jiaqi, et al.
Published: (2025)

Quantum Equilibrium Propagation: Gradient-Descent Training of Quantum Systems
by: Scellier, Benjamin
Published: (2024)

Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradients
by: Krahn, Maximilian, et al.
Published: (2023)

Active Learning with Variational Quantum Circuits for Quantum Process Tomography
by: Yang, Jiaqi, et al.
Published: (2024)

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

Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances
by: Turati, Gloria, et al.
Published: (2023)

Noise-Induced Barren Plateaus in Variational Quantum Algorithms
by: Wang, Samson, et al.
Published: (2020)

Adversarial Effects on Expressibility and Trainability in Distributed Variational Quantum Algorithms
by: Sadhu, Abhishek, et al.
Published: (2026)

Barren Plateaus in Variational Quantum Computing
by: Larocca, Martin, et al.
Published: (2024)

Application of Langevin Dynamics to Advance the Quantum Natural Gradient Optimization Algorithm
by: Borysenko, Oleksandr, et al.
Published: (2024)

Stochastic Shadow Descent: Training Parametrized Quantum Circuits with Shadows of Gradients
by: Pramanik, Sayantan, et al.
Published: (2025)

Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?
by: Wang, Samson, et al.
Published: (2021)

Denoising Gradient Descent in Variational Quantum Algorithms
by: Simon, Lars, et al.
Published: (2024)

Quantum Phase Classification of Rydberg Atom Systems Using Resource-Efficient Variational Quantum Circuits and Classical Shadows
by: Ahuja, Hemish, et al.
Published: (2025)

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

Enhancing Quantum Variational Algorithms with Zero Noise Extrapolation via Neural Networks
by: Bhattacharjee, Subhasree, et al.
Published: (2024)

NAPA: Intermediate-level Variational Native-pulse Ansatz for Variational Quantum Algorithms
by: Liang, Zhiding, et al.
Published: (2022)

Q-Newton: Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent
by: Li, Pingzhi, et al.
Published: (2024)

On Quantum Natural Policy Gradients
by: Sequeira, André, et al.
Published: (2024)

Simulation of a Variational Quantum Perceptron using Grover's Algorithm
by: Innan, Nouhaila, et al.
Published: (2023)

Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits
by: Lee, Yu-Ting, et al.
Published: (2026)

Quantum-Assisted Support Vector Regression
by: Dalal, Archismita, et al.
Published: (2021)

Resource-Efficient Variational Quantum Classifier
by: Ptáček, Petr, et al.
Published: (2025)

Variational Quantum Optimization with Continuous Bandits
by: Wanner, Marc, et al.
Published: (2025)

The Efficiency Frontier: Classical Shadows versus Quantum Footage
by: Ma, Shuowei, et al.
Published: (2025)

Bayesian Parameter Shift Rule in Variational Quantum Eigensolvers
by: Pedrielli, Samuele, et al.
Published: (2025)

Adaptive Observation Cost Control for Variational Quantum Eigensolvers
by: Anders, Christopher J., et al.
Published: (2025)

Physics-Informed Bayesian Optimization of Variational Quantum Circuits
by: Nicoli, Kim A., et al.
Published: (2024)

Trainability Beyond Linearity in Variational Quantum Objectives
by: Ma, Gordon, et al.
Published: (2026)