Cover Image

Analysis of Thompson Sampling for Controlling Unknown Linear Diffusion Processes

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Faradonbeh, Mohamad Kazem Shirani, Shirani, Sadegh, Bayati, Mohsen
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Artificial Intelligence Systems and Control Dynamical Systems Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Joint Learning of Linear Time-Invariant Dynamical Systems
by: Modi, Aditya, et al.
Published: (2021)

Adaptive Neural-Operator Backstepping Control of a Benchmark Hyperbolic PDE
by: Lamarque, Maxence, et al.
Published: (2024)

Gain Scheduling with a Neural Operator for a Transport PDE with Nonlinear Recirculation
by: Lamarque, Maxence, et al.
Published: (2024)

Distributed Optimization via Energy Conservation Laws in Dilated Coordinates
by: Baranwal, Mayank, et al.
Published: (2024)

The Asymptotic Behavior of Attention in Transformers
by: Abella, Álvaro Rodríguez, et al.
Published: (2024)

Reservoir Predictive Path Integral Control for Unknown Nonlinear Dynamics
by: Inoue, Daisuke, et al.
Published: (2025)

Online Actuator Selection and Controller Design for Linear Quadratic Regulation with Unknown System Model
by: Ye, Lintao, et al.
Published: (2022)

Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems
by: Shin, Sungho, et al.
Published: (2022)

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control
by: Skifstad, Julian, et al.
Published: (2026)

Koopman-Assisted Reinforcement Learning
by: Rozwood, Preston, et al.
Published: (2024)

Neural Hamiltonian Operator
by: Qi, Qian
Published: (2025)

ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
by: Huang, Yilie, et al.
Published: (2026)

Neural Operators for Predictor Feedback Control of Nonlinear Delay Systems
by: Bhan, Luke, et al.
Published: (2024)

Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants
by: Fourati, Fares, et al.
Published: (2025)

Data-driven Nonlinear Model Reduction using Koopman Theory: Integrated Control Form and NMPC Case Study
by: Schulze, Jan C., et al.
Published: (2024)

Model-Based Reinforcement Learning Control of Reaction-Diffusion Problems
by: Schenk, Christina, et al.
Published: (2024)

Model Predictive Control of Hybrid Dynamical Systems
by: Sanfelice, Ricardo G., et al.
Published: (2026)

Data-Driven Adversarial Online Control for Unknown Linear Systems
by: Liu, Zishun, et al.
Published: (2023)

Safe and Near-Optimal Control with Online Dynamics Learning
by: Prajapat, Manish, et al.
Published: (2025)

Bucketized Active Sampling for Learning ACOPF
by: Klamkin, Michael, et al.
Published: (2022)

Intersection of Reinforcement Learning and Bayesian Optimization for Intelligent Control of Industrial Processes: A Safe MPC-based DPG using Multi-Objective BO
by: Esfahani, Hossein Nejatbakhsh, et al.
Published: (2025)

Thompson Sampling in Partially Observable Contextual Bandits
by: Park, Hongju, et al.
Published: (2024)

Fitted Q-Iteration via Max-Plus-Linear Approximation
by: Liu, Y., et al.
Published: (2024)

Provably Safe Generative Sampling with Constricting Barrier Functions
by: Gadginmath, Darshan, et al.
Published: (2026)

Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms
by: Mohammadi, Hesameddin, et al.
Published: (2022)

Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
by: Adibi, Arman, et al.
Published: (2024)

Safe and Robust Domains of Attraction for Discrete-Time Systems: A Set-Based Characterization and Certifiable Neural Network Estimation
by: Serry, Mohamed, et al.
Published: (2026)

SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning
by: Zolman, Nicholas, et al.
Published: (2024)

Stability properties of gradient flow dynamics for the symmetric low-rank matrix factorization problem
by: Mohammadi, Hesameddin, et al.
Published: (2024)

Learning Dissipative Neural Dynamical Systems
by: Xu, Yuezhu, et al.
Published: (2023)

Observability conditions for neural state-space models with eigenvalues and their roots of unity
by: Gracyk, Andrew
Published: (2025)

Safely Learning Dynamical Systems
by: Ahmadi, Amir Ali, et al.
Published: (2023)

From exponential to finite/fixed-time stability: Applications to optimization
by: Ozaslan, Ibrahim K., et al.
Published: (2024)

Identifiability of Differential-Algebraic Systems
by: Montanari, Arthur N., et al.
Published: (2024)

A PAC-Bayes Approach for Controlling Unknown Linear Discrete-time Systems
by: Luo, Yujia, et al.
Published: (2026)

Sublinear Regret for a Class of Continuous-Time Linear-Quadratic Reinforcement Learning Problems
by: Huang, Yilie, et al.
Published: (2024)

Generative AI and Process Systems Engineering: The Next Frontier
by: Decardi-Nelson, Benjamin, et al.
Published: (2024)

Data-Driven Exploration for a Class of Continuous-Time Indefinite Linear--Quadratic Reinforcement Learning Problems
by: Huang, Yilie, et al.
Published: (2025)

Enhanced-FQL($λ$), an Efficient and Interpretable RL with novel Fuzzy Eligibility Traces and Segmented Experience Replay
by: Jalaeian-Farimani, Mohsen, et al.
Published: (2026)

Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling
by: Zhu, Feng, et al.
Published: (2025)