Cover Image

Quantum Algorithm for Sparse Online Learning with Truncated Gradient Descent

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lim, Debbie, Qiu, Yixian, Rebentrost, Patrick, Wang, Qisheng
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Quantum Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hybrid Quantum-Classical Algorithm For Robust Optimization via Stochastic-Gradient Online Learning
by: Lim, Debbie, et al.
Published: (2023)

Quantum Algorithms for the Pathwise Lasso
by: Doriguello, Joao F., et al.
Published: (2023)

Quantum Learning with Tunable Loss Functions
by: Qiu, Yixian, et al.
Published: (2025)

The Quantum Esscher Transform
by: Qiu, Yixian, et al.
Published: (2024)

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

Post-variational quantum neural networks
by: Huang, Po-Wei, et al.
Published: (2023)

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

Quantum Tilted Loss in Variational Optimization: Theory and Applications
by: Qiu, Yixian, et al.
Published: (2026)

Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games
by: Gao, Minbo, et al.
Published: (2023)

Accelerating Inference for Multilayer Neural Networks with Quantum Computers
by: Rattew, Arthur G., et al.
Published: (2025)

A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model
by: Ambainis, Andris, et al.
Published: (2025)

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

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

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

Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers
by: Du, Yuxuan, et al.
Published: (2025)

Concept learning of parameterized quantum models from limited measurements
by: Gan, Beng Yee, et al.
Published: (2024)

Quantum Algorithm for Apprenticeship Learning
by: Ambainis, Andris, et al.
Published: (2025)

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

Online Learning of Pure States is as Hard as Mixed States
by: Meyer, Maxime, et al.
Published: (2025)

Fundamentals of Quantum Machine Learning and Robustness
by: Pira, Lirandë, et al.
Published: (2026)

Quantum Algorithms for Projection-Free Sparse Convex Optimization
by: He, Jianhao, et al.
Published: (2025)

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

Classical and Quantum Speedups for Non-Convex Optimization via Energy Conserving Descent
by: Sun, Yihang, et al.
Published: (2026)

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

Adaptive Online Learning of Quantum States
by: Chen, Xinyi, et al.
Published: (2022)

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

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

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

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

Hybrid Heuristic Algorithms for Adiabatic Quantum Machine Learning Models
by: Alidaee, Bahram, et al.
Published: (2024)

An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-based Gradients
by: Wiedmann, Marco, et al.
Published: (2023)

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

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

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

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

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

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

Energy Scale Degradation in Sparse Quantum Solvers: A Barrier to Quantum Utility
by: Dinh, Thang N., et al.
Published: (2025)

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

Efficient Quantum Gradient and Higher-order Derivative Estimation via Generalized Hadamard Test
by: Li, Dantong, et al.
Published: (2024)