publications

2023

1. AIR

   A survey of Bayesian Network structure learning

   Neville K Kitson, Anthony C Constantinou, Zhigao Guo, and 2 more authors

   Artificial Intelligence Review 2023

   Bib PDF

   @article{kitson2021survey,
     title = {A survey of Bayesian Network structure learning},
     author = {Kitson, Neville K and Constantinou, Anthony C and Guo, Zhigao and Liu, Yang and Chobtham, Kiattikun},
     journal = {Artificial Intelligence Review},
     page = {1-94},
     year = {2023}
   }

2. ICLR

   Improving the imputation of missing data with Markov Blanket discovery

   Yang Liu, and Anthony C Constantinou

   In The Eleventh International Conference on Learning Representations 2023

   Bib PDF Code

   @inproceedings{liu2023improving,
     title = {Improving the imputation of missing data with Markov Blanket discovery},
     author = {Liu, Yang and Constantinou, Anthony C},
     booktitle = {The Eleventh International Conference on Learning Representations},
     year = {2023}
   }

3. Open problems in causal structure learning: A case study of COVID-19 in the UK

   Anthony C Constantinou, Neville K Kitson, Yang Liu, and 5 more authors

   Expert Systems with Applications 2023

   Bib PDF

   @article{constantinou2023open,
     title = {Open problems in causal structure learning: A case study of COVID-19 in the UK},
     author = {Constantinou, Anthony C and Kitson, Neville K and Liu, Yang and Chobtham, Kiattikun and Amirkhizi, Arian Hashemzadeh and Nanavati, Praharsh A and Mbuvha, Rendani and Petrungaro, Bruno},
     journal = {Expert Systems with Applications},
     pages = {121069},
     year = {2023},
     publisher = {Elsevier}
   }

2022

1. MLJ

   Greedy structure learning from data that contain systematic missing values

   Yang Liu, and Anthony C Constantinou

   Machine Learning 2022

   Bib PDF Code

   @article{liu2022greedy,
     title = {Greedy structure learning from data that contain systematic missing values},
     author = {Liu, Yang and Constantinou, Anthony C},
     journal = {Machine Learning},
     volume = {111},
     number = {10},
     pages = {3867--3896},
     year = {2022},
     publisher = {Springer US},
   }

2. IJAR

   Effective and efficient structure learning with pruning and model averaging strategies

   Anthony C Constantinou, Yang Liu, Neville K Kitson, and 2 more authors

   International Journal of Approximate Reasoning 2022

   Bib PDF

   @article{constantinou2022effective,
     title = {Effective and efficient structure learning with pruning and model averaging strategies},
     author = {Constantinou, Anthony C and Liu, Yang and Kitson, Neville K and Chobtham, Kiattikun and Guo, Zhigao},
     journal = {International Journal of Approximate Reasoning},
     volume = {151},
     pages = {292--321},
     year = {2022},
     publisher = {Elsevier}
   }

3. JMLR

   Improving Bayesian network structure learning in the presence of measurement error

   Yang Liu, Anthony C Constantinou, and Zhigao Guo

   Journal of Machine Learning Research 2022

   Bib PDF Code

   @article{liu2022improving,
     title = {Improving Bayesian network structure learning in the presence of measurement error},
     author = {Liu, Yang and Constantinou, Anthony C and Guo, Zhigao},
     journal = {Journal of Machine Learning Research},
     volume = {23},
     number = {324},
     pages = {1--28},
     year = {2022},
     publisher = {Journal of Machine Learning Research,},
   }

4. OSNEM

   SWSR: A Chinese dataset and lexicon for online sexism detection

   Aiqi Jiang, Xiaohan Yang, Yang Liu, and 1 more author

   Online Social Networks and Media, 2022

   Bib PDF

   @article{jiang2022swsr,
     title = {SWSR: A Chinese dataset and lexicon for online sexism detection},
     author = {Jiang, Aiqi and Yang, Xiaohan and Liu, Yang and Zubiaga, Arkaitz},
     journal = {Online Social Networks and Media,},
     volume = {27},
     pages = {100182},
     year = {2022},
     publisher = {Elsevier,},
   }

2021

1. IJAR

   Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data

   Anthony C Constantinou, Yang Liu, Kiattikun Chobtham, and 2 more authors

   International Journal of Approximate Reasoning 2021

   Bib PDF

   @article{constantinou2021large,
     title = {Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data},
     author = {Constantinou, Anthony C and Liu, Yang and Chobtham, Kiattikun and Guo, Zhigao and Kitson, Neville K},
     journal = {International Journal of Approximate Reasoning},
     volume = {131},
     pages = {151--188},
     year = {2021},
     publisher = {Elsevier}
   }

2020

1. The Bayesys data and Bayesian network repository

   Anthony C Constantinou, Yang Liu, Kiattikun Chobtham, and 2 more authors

   Queen Mary University of London: London, UK 2020

   Bib PDF

   @article{constantinou2020bayesys,
     title = {The Bayesys data and Bayesian network repository},
     author = {Constantinou, Anthony C and Liu, Yang and Chobtham, Kiattikun and Guo, Zhigao and Kitson, Neville K},
     journal = {Queen Mary University of London: London, UK},
     year = {2020}
   }