Quantum Non-Linear Bandit Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Siam, Zakaria Shams, Guan, Chaowen, Liu, Chong |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Enhancing the Trainability of Variational Quantum Circuits with Regularization Strategies
by: Zhuang, Jun, et al.
Published: (2024)
by: Zhuang, Jun, et al.
Published: (2024)
Multi-Objective Coverage via Constraint Active Search
by: Siam, Zakaria Shams, et al.
Published: (2026)
by: Siam, Zakaria Shams, et al.
Published: (2026)
Large Language Models Can Help Mitigate Barren Plateaus in Quantum Neural Networks
by: Zhuang, Jun, et al.
Published: (2025)
by: Zhuang, Jun, et al.
Published: (2025)
Variational Quantum Optimization with Continuous Bandits
by: Wanner, Marc, et al.
Published: (2025)
by: Wanner, Marc, et al.
Published: (2025)
Quantum Algorithms for Non-smooth Non-convex Optimization
by: Liu, Chengchang, et al.
Published: (2024)
by: Liu, Chengchang, et al.
Published: (2024)
Non-native Quantum Generative Optimization with Adversarial Autoencoders
by: Wilson, Blake A., et al.
Published: (2024)
by: Wilson, Blake A., et al.
Published: (2024)
Benchmarking VQE Configurations: Architectures, Initializations, and Optimizers for Silicon Ground State Energy
by: Boutakka, Zakaria, et al.
Published: (2025)
by: Boutakka, Zakaria, et al.
Published: (2025)
Quantum-Enhanced Neural Contextual Bandit Algorithms
by: Huang, Yuqi, et al.
Published: (2026)
by: Huang, Yuqi, et al.
Published: (2026)
GSC-QEMit: A Telemetry-Driven Hierarchical Forecast-and-Bandit Framework for Adaptive Quantum Error Mitigation
by: Szachara, Steven, et al.
Published: (2026)
by: Szachara, Steven, et al.
Published: (2026)
Adaptive Learning for Quantum Linear Regression
by: Carugno, Costantino, et al.
Published: (2024)
by: Carugno, Costantino, et al.
Published: (2024)
Multi-Armed Bandits and Quantum Channel Oracles
by: Buchholz, Simon, et al.
Published: (2023)
by: Buchholz, Simon, et al.
Published: (2023)
Trainability Beyond Linearity in Variational Quantum Objectives
by: Ma, Gordon, et al.
Published: (2026)
by: Ma, Gordon, et al.
Published: (2026)
Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm
by: Liang, Zhiding, et al.
Published: (2024)
by: Liang, Zhiding, et al.
Published: (2024)
Quantum-Powered Personalized Learning
by: Zhou, Yifan, et al.
Published: (2024)
by: Zhou, Yifan, et al.
Published: (2024)
Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits
by: Du, Yuxuan, et al.
Published: (2024)
by: Du, Yuxuan, et al.
Published: (2024)
Simulating Non-Markovian Open Quantum Dynamics with Neural Quantum States
by: Cao, Long, et al.
Published: (2024)
by: Cao, Long, et al.
Published: (2024)
Quantum Circuit Optimization with AlphaTensor
by: Ruiz, Francisco J. R., et al.
Published: (2024)
by: Ruiz, Francisco J. R., et al.
Published: (2024)
Classical and Quantum Speedups for Non-Convex Optimization via Energy Conserving Descent
by: Sun, Yihang, et al.
Published: (2026)
by: Sun, Yihang, et al.
Published: (2026)
Characterizing Non-Markovian Dynamics of Open Quantum Systems
by: Reddy, Sohail
Published: (2025)
by: Reddy, Sohail
Published: (2025)
Non-Linear Strong Data-Processing for Quantum Hockey-Stick Divergences
by: Nuradha, Theshani, et al.
Published: (2025)
by: Nuradha, Theshani, et al.
Published: (2025)
Neural Guided Sampling for Quantum Circuit Optimization
by: Rosenhahn, Bodo, et al.
Published: (2025)
by: Rosenhahn, Bodo, et al.
Published: (2025)
Bandits roaming Hilbert space
by: Lumbreras, Josep
Published: (2025)
by: Lumbreras, Josep
Published: (2025)
Quantum Gaussian Process Regression for Bayesian Optimization
by: Rapp, Frederic, et al.
Published: (2023)
by: Rapp, Frederic, et al.
Published: (2023)
Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits
by: Yu, Zhan, et al.
Published: (2023)
by: Yu, Zhan, et al.
Published: (2023)
Quantum Algorithms for Projection-Free Sparse Convex Optimization
by: He, Jianhao, et al.
Published: (2025)
by: He, Jianhao, et al.
Published: (2025)
Differentiable Logical Programming for Quantum Circuit Discovery and Optimization
by: Sulc, Antonin
Published: (2026)
by: Sulc, Antonin
Published: (2026)
WSBD: Freezing-Based Optimizer for Quantum Neural Networks
by: Kverne, Christopher, et al.
Published: (2026)
by: Kverne, Christopher, et al.
Published: (2026)
Quantum End-to-End Learning for Contextual Combinatorial Optimization
by: Lee, Jaehwan, et al.
Published: (2026)
by: Lee, Jaehwan, et al.
Published: (2026)
Physics-Informed Bayesian Optimization of Variational Quantum Circuits
by: Nicoli, Kim A., et al.
Published: (2024)
by: Nicoli, Kim A., et al.
Published: (2024)
A Versatile Variational Quantum Kernel Framework for Non-Trivial Classification
by: Yuhan, Jiang, et al.
Published: (2025)
by: Yuhan, Jiang, et al.
Published: (2025)
Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates
by: Grewal, Sabee, et al.
Published: (2023)
by: Grewal, Sabee, et al.
Published: (2023)
Compilation, Optimization, Error Mitigation, and Machine Learning in Quantum Algorithms
by: Wang, Shuangbao Paul, et al.
Published: (2025)
by: Wang, Shuangbao Paul, et al.
Published: (2025)
Geometric Preconditioning and Curriculum Optimization for Trainable Variational Quantum Regression
by: Meng, Qingyu, et al.
Published: (2026)
by: Meng, Qingyu, et al.
Published: (2026)
Hamiltonian-based Quantum Reinforcement Learning for Neural Combinatorial Optimization
by: Kruse, Georg, et al.
Published: (2024)
by: Kruse, Georg, et al.
Published: (2024)
Quantum Re-Uploading for Calorimetry: Optimized Architectures with Extended Expressivity
by: Cassé, Léa, et al.
Published: (2024)
by: Cassé, Léa, et al.
Published: (2024)
The Stabilizer Bootstrap of Quantum Machine Learning with up to 10000 qubits
by: Li, Yuqing, et al.
Published: (2024)
by: Li, Yuqing, et al.
Published: (2024)
Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealer
by: Hagiwara, Ryo, et al.
Published: (2025)
by: Hagiwara, Ryo, et al.
Published: (2025)
PALQO: Physics-informed Model for Accelerating Large-scale Quantum Optimization
by: Huang, Yiming, et al.
Published: (2025)
by: Huang, Yiming, et al.
Published: (2025)
Quantum-Enhanced Weight Optimization for Neural Networks Using Grover's Algorithm
by: Jura, Stefan-Alexandru, et al.
Published: (2025)
by: Jura, Stefan-Alexandru, et al.
Published: (2025)
Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension
by: Lee, Changwon, et al.
Published: (2024)
by: Lee, Changwon, et al.
Published: (2024)
Similar Items
-
Enhancing the Trainability of Variational Quantum Circuits with Regularization Strategies
by: Zhuang, Jun, et al.
Published: (2024) -
Multi-Objective Coverage via Constraint Active Search
by: Siam, Zakaria Shams, et al.
Published: (2026) -
Large Language Models Can Help Mitigate Barren Plateaus in Quantum Neural Networks
by: Zhuang, Jun, et al.
Published: (2025) -
Variational Quantum Optimization with Continuous Bandits
by: Wanner, Marc, et al.
Published: (2025) -
Quantum Algorithms for Non-smooth Non-convex Optimization
by: Liu, Chengchang, et al.
Published: (2024)