Xuan Zhang
Orcid: 0000-0002-8828-7442Affiliations:
- University of Agder, Grimstad, Norway
According to our database1,
Xuan Zhang
authored at least 28 papers
between 2011 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
MDTNet: Partial transformer with degradation-aware module for restoring old photos with multiple degradations.
Neurocomputing, 2025
2024
The Hierarchical Discrete Pursuit Learning Automaton: A Novel Scheme With Fast Convergence and Epsilon-Optimality.
IEEE Trans. Neural Networks Learn. Syst., June, 2024
2023
IEEE Trans. Pattern Anal. Mach. Intell., May, 2023
CoRR, 2023
Interpretable Tsetlin Machine-based Premature Ventricular Contraction Identification.
CoRR, 2023
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
2022
IEEE Trans. Pattern Anal. Mach. Intell., 2022
A Comprehensive Survey of Estimator Learning Automata and Their Recent Convergence Results.
Proceedings of the Advances in Computing, Informatics, Networking and Cybersecurity, 2022
The Hierarchical Discrete Learning Automaton Suitable for Environments with Many Actions and High Accuracy Requirements.
Proceedings of the AI 2021: Advances in Artificial Intelligence, 2022
2021
2020
A Conclusive Analysis of the Finite-Time Behavior of the Discretized Pursuit Learning Automaton.
IEEE Trans. Neural Networks Learn. Syst., 2020
The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.
IEEE Trans. Neural Networks Learn. Syst., 2020
Adaptive Continuous Feature Binarization for Tsetlin Machines Applied to Forecasting Dengue Incidences in the Philippines.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020
2019
A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks.
Proceedings of the Advances and Trends in Artificial Intelligence. From Theory to Practice, 2019
2018
The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions.
Proceedings of the Artificial Intelligence Applications and Innovations, 2018
2017
The design of absorbing Bayesian pursuit algorithms and the formal analyses of their ε-optimality.
Pattern Anal. Appl., 2017
2016
Appl. Intell., 2016
Optimizing channel selection for cognitive radio networks using a distributed Bayesian learning automata-based approach.
Appl. Intell., 2016
2014
A formal proof of the ε-optimality of absorbing continuous pursuit algorithms using the theory of regular functions.
Appl. Intell., 2014
Using the Theory of Regular Functions to Formally Prove the ε-Optimality of Discretized Pursuit Learning Algorithms.
Proceedings of the Modern Advances in Applied Intelligence, 2014
A Bayesian Learning Automata-Based Distributed Channel Selection Scheme for Cognitive Radio Networks.
Proceedings of the Modern Advances in Applied Intelligence, 2014
2013
On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata.
Appl. Intell., 2013
Channel selection in Cognitive Radio Networks: A Switchable Bayesian Learning Automata approach.
Proceedings of the 24th IEEE Annual International Symposium on Personal, 2013
On Using the Theory of Regular Functions to Prove the <i>ε</i>-Optimality of the Continuous Pursuit Learning Automaton.
Proceedings of the Recent Trends in Applied Artificial Intelligence, 2013
2012
Proceedings of the Advanced Research in Applied Artificial Intelligence, 2012
2011
Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems.
Proceedings of the Artificial Intelligence Applications and Innovations, 2011
Proceedings of the Modern Approaches in Applied Intelligence, 2011