Xuan Zhang

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 20

Top Topics

Learning Automaton

Cognitive Radio

Convergence Rate

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

Rebekka Olsson Omslandseter, Lei Jiao, Xuan Zhang, Anis Yazidi, B. John Oommen
The Hierarchical Discrete Pursuit Learning Automaton: A Novel Scheme With Fast Convergence and Epsilon-Optimality. IEEE Trans. Neural Networks Learn. Syst. 35 (6) (2024)
Kuruge Darshana Abeyrathna, Ahmed Abdulrahem Othman Abouzeid, Bimal Bhattarai, Charul Giri, Sondre Glimsdal, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Jivitesh Sharma, Svein Anders Tunheim, Xuan Zhang
Building Concise Logical Patterns by Constraining Tsetlin Machine Clause Size. IJCAI (2023)
Ole-Christoffer Granmo, Per-Arne Andersen, Lei Jiao, Xuan Zhang, Christian D. Blakely, Tor Oddbjørn Tveit
Learning Minimalistic Tsetlin Machine Clauses with Markov Boundary-Guided Pruning. CoRR (2023)
Kuruge Darshana Abeyrathna, Ahmed Abdulrahem Othman Abouzeid, Bimal Bhattarai, Charul Giri, Sondre Glimsdal, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Jivitesh Sharma, Svein Anders Tunheim, Xuan Zhang
Building Concise Logical Patterns by Constraining Tsetlin Machine Clause Size. CoRR (2023)
Lei Jiao, Xuan Zhang, Ole-Christoffer Granmo, Kuruge Darshana Abeyrathna
On the Convergence of Tsetlin Machines for the XOR Operator. IEEE Trans. Pattern Anal. Mach. Intell. 45 (5) (2023)
B. John Oommen, Xuan Zhang, Lei Jiao
A Comprehensive Survey of Estimator Learning Automata and Their Recent Convergence Results. Honoring Professor Mohammad S. Obaidat (2022)
Rebekka Olsson Omslandseter, Lei Jiao, Xuan Zhang, Anis Yazidi, B. John Oommen
The Hierarchical Discrete Learning Automaton Suitable for Environments with Many Actions and High Accuracy Requirements. AI (2022)
Xuan Zhang, Lei Jiao, Ole-Christoffer Granmo, Morten Goodwin
On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators. IEEE Trans. Pattern Anal. Mach. Intell. 44 (10) (2022)
Lei Jiao, Xuan Zhang, Ole-Christoffer Granmo, Kuruge Darshana Abeyrathna
On the Convergence of Tsetlin Machines for the XOR Operator. CoRR (2021)
Lei Jiao, Xuan Zhang, Ole-Christoffer Granmo
On the Convergence of Tsetlin Machines for the AND and the OR Operators. CoRR (2021)
Xuan Zhang, Lei Jiao, Ole-Christoffer Granmo, Morten Goodwin
On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators. CoRR (2020)
Kuruge Darshana Abeyrathna, Ole-Christoffer Granmo, Xuan Zhang, Morten Goodwin
Adaptive Continuous Feature Binarization for Tsetlin Machines Applied to Forecasting Dengue Incidences in the Philippines. SSCI (2020)
Xuan Zhang, Lei Jiao, B. John Oommen, Ole-Christoffer Granmo
A Conclusive Analysis of the Finite-Time Behavior of the Discretized Pursuit Learning Automaton. IEEE Trans. Neural Networks Learn. Syst. 31 (1) (2020)
Anis Yazidi, Xuan Zhang, Lei Jiao, B. John Oommen
The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions. IEEE Trans. Neural Networks Learn. Syst. 31 (2) (2020)
Kuruge Darshana Abeyrathna, Ole-Christoffer Granmo, Xuan Zhang, Morten Goodwin
A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks. IEA/AIE (2019)
Kuruge Darshana Abeyrathna, Ole-Christoffer Granmo, Xuan Zhang, Morten Goodwin
A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks. CoRR (2019)
Anis Yazidi, Xuan Zhang, Lei Jiao, B. John Oommen
The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions. AIAI (2018)
Xuan Zhang, B. John Oommen, Ole-Christoffer Granmo
The design of absorbing Bayesian pursuit algorithms and the formal analyses of their ε-optimality. Pattern Anal. Appl. 20 (3) (2017)
Lei Jiao, Xuan Zhang, B. John Oommen, Ole-Christoffer Granmo
Optimizing channel selection for cognitive radio networks using a distributed Bayesian learning automata-based approach. Appl. Intell. 44 (2) (2016)
Xuan Zhang, B. John Oommen, Ole-Christoffer Granmo, Lei Jiao
A formal proof of the 𝜀-optimality of discretized pursuit algorithms. Appl. Intell. 44 (2) (2016)
Xuan Zhang, Ole-Christoffer Granmo, B. John Oommen, Lei Jiao
A formal proof of the ε-optimality of absorbing continuous pursuit algorithms using the theory of regular functions. Appl. Intell. 41 (3) (2014)
Lei Jiao, Xuan Zhang, Ole-Christoffer Granmo, B. John Oommen
A Bayesian Learning Automata-Based Distributed Channel Selection Scheme for Cognitive Radio Networks. IEA/AIE (2) (2014)
Xuan Zhang, B. John Oommen, Ole-Christoffer Granmo, Lei Jiao
Using the Theory of Regular Functions to Formally Prove the ε-Optimality of Discretized Pursuit Learning Algorithms. IEA/AIE (1) (2014)
Xuan Zhang, Ole-Christoffer Granmo, B. John Oommen, Lei Jiao
-Optimality of the Continuous Pursuit Learning Automaton. IEA/AIE (2013)
Xuan Zhang, Ole-Christoffer Granmo, B. John Oommen
On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata. Appl. Intell. 39 (4) (2013)
Xuan Zhang, Lei Jiao, Ole-Christoffer Granmo, B. John Oommen
Channel selection in Cognitive Radio Networks: A Switchable Bayesian Learning Automata approach. PIMRC (2013)
Xuan Zhang, Ole-Christoffer Granmo, B. John Oommen
Discretized Bayesian Pursuit - A New Scheme for Reinforcement Learning. IEA/AIE (2012)
Xuan Zhang, Ole-Christoffer Granmo, B. John Oommen
The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata. IEA/AIE (2) (2011)
Xuan Zhang, B. John Oommen, Ole-Christoffer Granmo
Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems. EANN/AIAI (2) (2011)