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  PUBLICATIONS

 

 

Publications are sorted by year as either Journal ( J ), Conference ( C ), Academic Technical Report ( TR ), Industry Technical Report ( ITR ), or Thesis ( T ).

   

 

2020

C [1]

Guo, Z. and Constantinou, A. C. (2020). Approximate learning of high dimensional Bayesian network structures via pruning of Candidate Parent Sets. arXiv:2006.04753 [cs.AI]


C [2]

Chobtham, K. and Constantinou, A. C. (2020). Bayesian network structure learning with causal effects in the presence of latent variables. arXiv:2005.14381 [cs.LG]

 

J [3]

Constantinou, A. C., Liu, Y., Chobtham, K., Guo, Z., and Kitson, N. K. (2020). Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data. arXiv:2005.09020 [cs.LG]


J [4]

Constantinou, A. C. (2020). Learning Bayesian Networks that enable full propagation of evidence. arXiv:2004.04571 [cs.LG]


J [5]

Kitson, N. K., & Constantinou, A. (2020). Learning Bayesian networks from demographic and health survey data. Under review, arXiv:1912.00715 [cs.AI]

 

J [6]

Constantinou, A. (2020). Asian handicap football betting with rating-based hybrid Bayesian networks. arXiv:2003.09384 [stat.AP]


TR [7]

Constantinou, A. C., Liu, Y., Chobtham, K., Guo, Z., and Kitson, N. K. (2020). The Bayesys data and Bayesian network repository. Queen Mary University of London, London, UK. [Online]. Available: http://bayesian-ai.eecs.qmul.ac.uk/bayesys/ and http://www.bayesys.com

 

J [8]

Fenton, N., Neil, M., & Constantinou, A. (2020). The Book of Why: The New Science of Cause and Effect, Judea Pearl, Dana Mackenzie, Basic Books (2018). Artificial Intelligence, vol. 284, 103286.

 

J [9]

Constantinou, A. C. (2020). Learning Bayesian Networks with the Saiyan Algorithm. ACM Transactions on Knowledge Discovery from Data, vol. 14, Iss. 4, Article 44.

 

 

2019

TR [10]

Constantinou, A. (2019). The Bayesys user manual. Queen Mary University of London, London, UK. [Online]. Available: http://bayesian-ai.eecs.qmul.ac.uk/bayesys/ and http://www.bayesys.com

 
J [11]

Constantinou, A. (2019). Evaluating structure learning algorithms with a balanced scoring function. arXiv:1905.12666 [cs.LG].


ITR [12]

Constantinou, A. (2019). Rating-based Golf Tournament Simulation. Deliverable Technical Report under Collaboration NO:24.20181101.


J [13]

Constantinou, A. C. (2019). The importance of temporal information when learning Bayesian networks. Under review.

 
J [14] Constantinou, A., Fenton, N., & Neil, M. (2019). How do some Bayesian Network machine learned graphs compare to causal knowledge? Under review.
   

 

2018

ITR [15]

Constantinou, A. (2018). As assessment of set-based ratings in capturing player ability in tennis. Deliverable Technical Report under Collaboration NO:23.20180911.


TR [16]

Constantinou, A. (2018). Bayesian Artificial Intelligence for Decision Making under Uncertainty. Engineering and Physical Sciences Research Council, EP/S001646/1. [PDF]


J [17]

Constantinou, A. (2018). Dolores: A model that predicts football match outcomes from all over the world. Machine Learning, pp. 1–27. [Free view, DOI, draft]

 

Dolores ranked 2nd in the international special issue competition Machine Learning for Soccer. Discussed in Prof. Fenton's Probability and Risk blog.


J [18]

Constantinou, A., & Fenton, N. (2018). Things to know about Bayesian Networks. Significance, vol. 15, Iss. 2, pp. 19–23. [Open Access DOI, PDF]

 

Top 20 most downloaded paper in Significance for 2017 and 2018

 

ITR [19]

Constantinou, A. (2018). Tennis player ratings based on points won and lost when serving and returning. Deliverable Technical Report under Collaboration NO:22.20180524.


J [20]

Yet, B., Neil, M., Fenton, N., Constantinou, A., & Dementiev, E. (2018). An Improved Method for Solving Hybrid Influence Diagrams. International Journal of Approximate Reasoning, vol. 95, pp. 93–112. [draft, DOI]


 
J [21]

Yet, B., Constantinou, A., Fenton, N., & Neil, M. (2018). Expected Value of Partial Perfect Information in Hybrid Models using Dynamic Discretization. IEEE Access, vol. 6, pp. 7802–7817.  [draft, DOI]


 
ITR [22] Constantinou, A. (2018). Temporal modelling and match prediction in Darts. Deliverable Technical Report under Collaboration NO:21.20171114.  
   

 

2017

 
C [23]

Fenton, N., Constantinou, A., & Neil, M. (2017). Combining judgments with messy data to build Bayesian Network models for improved intelligence analysis and decision support. In Proceedings of the 26th conference on Subjective Probability, Utility and Decision Making (SPUDM 26), Haifa, Israel, August 20-24. [long abstract, slides]


 
J [24]

Constantinou, A. C., & Fenton, N. (2017). The future of the London Buy-To-Let property market: Simulation with Temporal Bayesian Networks. PLoS ONE, 12(6): e0179297 [Open Access DOI, PDF]


 
J [25] Constantinou, A., & Fenton, N. (2017). Towards Smart-Data: Improving predictive accuracy in long-term football team performance. Knowledge-Based Systems, vol. 124, pp 93–104. [DOI, draft]
 
   

 

2016

 
C [26]

Constantinou, A., & Fenton, N. (2016). Improving predictive accuracy using Smart-Data rather than Big-Data: A case study of soccer teams’ evolving performance. In Proceedings of the 13th UAI Bayesian Modeling Applications Workshop (BMAW 2016), 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), New York City, USA, June 25-29, 2016, pp. 54–59. [extended abstract, slides]


 
J [27]

Constantinou, A., Fenton, N., & Neil, M. (2016). Integrating expert knowledge with data in causal probabilistic networks: Preserving data-driven expectations when the expert variables remain unobserved. Expert Systems with Applications, vol. 56, pp. 197–208. [DOI, draft]


 
J [28]

Fenton, N., Neil, M., Lagnado, D., Marsh, W., Yet, B., & Constantinou, A. (2016). How to model mutually exclusive events based on independent causal pathways in Bayesian network models. Knowledge-Based Systems, vol. 113, 39–50. [Open Access DOI, PDF]


 
ITR [29]

Constantinou, A. (2016). Generic Bayesian football predictions based on discrepancies in strength between adversaries. Deliverable Technical Report for Venture Sports & Events Co. Ltd under Collaboration NO:20.SPORTS-BETTING.09/05/2016.


 
J [30]

Constantinou, A., Fenton, N., Marsh, W. & Radlinski, L. (2016). From complex questionnaire and interviewing data to intelligent Bayesian models for medical decision support. Artificial Intelligence in Medicine, vol. 60, pp. 75–93. [DOI, draft]

 

Discussed in Atlas of Science. Also discussed in Prof. Fenton's Probability and Risk blog.


J [31]

Yet, B., Constantinou, A., Fenton, N., Neil, M., Luedeling, E., & Shepherd, K. (2016). A Bayesian Network Framework for Project Cost, Benefit and Risk Analysis with an Agricultural Development Case Study. Expert Systems with Applications, vol. 60, 141–155. [DOI, draft].

 

Discussed in CGIAR Water, Land and Ecosystems (WLE).


ITR [32]

Constantinou, A. (2016). Bayesian modelling and dynamic ratings for national football team assessment: The case of EURO 2016. Deliverable Technical Report for Venture Sports & Events Co. Ltd under Collaboration NO:20.SPORTS-BETTING.09/05/2016.


 
J [33]

Constantinou, A., Yet, B., Fenton, N., Neil, M., & Marsh, W. (2016). Value of Information analysis for Interventional and Counterfactual Bayesian networks in Forensic Medical Sciences.  Artificial Intelligence in Medicine, vol. 66, pp. 41–52. [DOI, draft].

 

Discussed in Atlas of Science and in Prof. Fenton's Probability and Risk blog.


 
C [34] Constantinou, A., & Fenton, N. (2016). Smart data – not just big data: Real-world decision making with Bayesian networks. SETforBRITAIN 2016, Engineering and Mathematical Sciences Exhibition, House of Commons, Parliament, Westminster, London, UK, March 7, 2016. [poster]

 
J [35] Coid, J. W., Ullrich S., Kallis, C., Freestone, M., Gonzalez, R., Bui, L., et al. (2016). Improving risk management for violence in mental health services: a multimethods approach. Programme Grants for Applied Research, vol. 4, Iss. 16. [DOI, PDF].

ITR [36] Constantinou, A. (2016). Extending Bayesian Networks and Dynamic Rating Systems to the German, French and Spanish football leagues. Deliverable Technical Report for Venture Sports & Events Co. Ltd under Collaboration NO:19.SPORTS-BETTING.26/02/2016.

ITR [37] Constantinou, A. (2016). An expert’s guide to providing subjective inputs for Bayesian Network football models. Deliverable Technical Report for Venture Sports & Events Co. Ltd under Collaboration NO:19.SPORTS-BETTING.26/02/2016.

 
TR [38] Constantinou, A., Fenton, N., Marsh, W., & Radlinski, L. (2016). From complex questionnaires and interviewing data to intelligent Bayesian Network models. Atlas of Science, 2016. [Online, PDF].

 
ITR [39]

Constantinou, A. (2016). Algorithmic rating for determining the current level of football team performance. Deliverable Technical Report for Venture Sports & Events Co. Ltd under Collaboration NO:18.SPORTS-BETTING.17/11/2015.


 
ITR [40] Constantinou, A. (2016). Bayesian network modelling for betting decision making of the Under/Over 2.5 Goals Scored outcomes. Deliverable Technical Report for Venture Sports & Events Co. Ltd under Collaboration NO:18.SPORTS-BETTING.17/11/2015.  
   

 

2015

 
TR [41]

Fenton, N., Neil, M., & Constantinou, A. (2015). Simpson’s Paradox and the implications for medical trials. arXiv:1912.01422 [stat.ME].

 

 
J [42]

Constantinou, A., Freestone, M., Marsh, W., & Coid, J. (2015). Causal inference for violence risk management and decision support in Forensic Psychiatry. Decision Support Systems, vol. 80, pp. 42–55. [DOI, draft].

 

 
J [43]

Constantinou, A., Freestone, M. F., Marsh, W., Coid, J., & Fenton, N. (2015). Risk assessment and risk management of violent reoffending among prisoners. Expert Systems with Applications, vol. 42, Iss. 21, pp. 7511–7529. [DOI, draft].

 

Discussed in Prof. Fenton's Probability and Risk blog.


 
C [44]

Yet, B., Constantinou, A., Fenton, N., Neil, M., Luedeling, E., & Shepherd, K. (2015). Project Cost, Benefit and Risk Analysis using Bayesian Networks. In Proceedings of the 12th UAI Bayesian Modeling Applications Workshop, 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), Amsterdam, Netherlands, July 12-16, 2015. [Abstract]


 
ITR [45]

Constantinou, A. (2015). Managing the risk of model overfitting when parameterising complex Bayesian networks with football data. Deliverable Technical Report for Venture Sports & Events Co. Ltd under Collaboration NO:18.SPORTS-BETTING.17/11/2015.


 
TR [46] Constantinou, A., Yet, B., Fenton, N., Neil, M., & Marsh, W. (2015). What is the value of missing information when assessing decisions that involve actions for intervention? Atlas of Science, 2015. [Online, PDF].

 
ITR [47] Constantinou, A. (2015). Bayesian network modelling for football match prediction of the Asian Handicap odds. Deliverable Technical Report for Venture Sports & Events Co. Ltd under Collaboration NO:17.BETTING.21/7/2015.

 
ITR [48] Constantinou, A., Yet, B., Fenton, N., & Neil, M. (2015). Bayesian Modelling Framework for Planning and Evaluating Agricultural Development Projects. Final Deliverable Report by Agena Ltd for ICRAF under Collaboration SD4/2012/214.  
   

 

2014

 
J [49]

Coid, J. W., Ullrich, S., Kallis, C., Freestone, M., Gonzalez, R., Bui, L., Igoumenou, A., Constantinou, A., Fenton, N., Marsh, W., Yang, M., DeStavola, B., Hu, J., Shaw, J., Doyle, M., Archer-Power, L., Davoren, M., Osumili, B., McCrone, P., Barrett, K., Hindle, D., Bebbington P. (2014). Improving Risk Management in Mental Health Services – A Multi-Methods Approach. The National Institute for Health Research (NIHR), UK 2014.


 
C [50]

Marsh, W., Constantinou, A., Yet, B., & Fenton, N. (2014). Evidence synthesis for patient-specific decision support using Bayesian networks. Life Sciences Conference: Population Health in a Post-Genomic Era, London, UK, December 2014.


 
J [51]

Constantinou, A., Fenton, N. E., & Pollock, L. J. H. (2014). Bayesian networks for unbiased assessment of referee bias in Association Football. Psychology of Sport and Exercise, vol. 15, Iss. 5, pp. 538–547. [DOI, draft].

 

Discussed in The Huffington Post and in Football Perspectives. Also discussed in Prof. Fenton's Probability and Risk blog.


 
C [52]

Constantinou, A., Freestone, M., & Coid, J. W. (2014). Development of a Bayesian network for violence risk management. 14th Annual Meeting of the International Association of Forensic Mental Health Services (IAFMHS), Toronto, Canada. June 2014.


 
C [53]

Coid, J. W., Constantinou, A., Freestone, M., Kallis, C., & Bui, L. (2014). Causal models for violence risk assessment and management: a new paradigm. 14th Annual Meeting of the International Association of Forensic Mental Health Services (IAFMHS), Toronto, Canada. June 2014.


 
C [54]

Constantinou, A., Freestone, M., & Coid, J. W. (2014). Using causal inference in risk analysis of violent re-offending among UK prisoners. 15th Annual Conference of the British and Irish Group for the Study of Personality Disorder (BIGSPD), Lincoln, UK. February 2014.


 
TR [55] Constantinou, A., Fenton, N. E., & Pollock, L. J. H. (2014). Bayesian networks for unbiased assessment of referee bias in football. Football Perspectives, 4 July, 2014 [Online].
 
   

 

2013

 
J [56]

Constantinou, A., & Fenton, N. E. (2013). Profiting from arbitrage and odds biases of the European gambling market. The Journal of Gambling Business and Economics, vol. 7, Iss. 2, pp. 41–70. [PDF]


TR [57]

Constantinou, A. (2013). Football: Win, Lose or Draw? Computer Science For Fun (CS4FN) [Online].


 
J [58]

Constantinou, A., Fenton, N. E., & Neil, M. (2013). Profiting from an Inefficient Association Football Gambling Market: Prediction, Risk and Uncertainty Using Bayesian Networks. Knowledge-Based Systems, vol. 50, pp. 60–86. [Open Access DOI, PDF].

 

Dedicated website: PI-Football.

 

 
J [59]

Constantinou, A., & Fenton, N. E. (2013). Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries. Journal of Quantitative Analysis in Sports, vol. 9, Iss. 1, pp. 37–50. [DOI, draft].

 

Dedicated website: PI-Football. Also discussed in Jona's Opisthokonta blog.

 

 
   

 

2012 (prior and during PhD)

 
T [60]

Constantinou, A. (2012). Bayesian Networks for Prediction, Risk Assessment and Decision Making in an inefficient Association Football gambling market. Ph.D Thesis, Risk & Information Management Research Group, School of Electronic Engineering and Computer Science, Queen Mary, University of London. Primary Supervision: Prof. Norman Fenton, Secondary Supervision: Prof. Martin Neil. September 2012. [Original version] [Restructured version (easier to read)].

 

 
ITR [61]

Constantinou, A. (2012). Professional business models based on football match odds. Technical Report for Agena Ltd, London, UK. August 2012.


 
J [62]

Constantinou, A., Fenton, N. E., & Neil, M. (2012). pi-football: A Bayesian network model for forecasting Association Football match outcomes. Knowledge-Based Systems, vol. 36, pp. 322339. [DOI, draft].

 

Discussed in CS4FN. Dedicated website: PI-Football.

 

 
J [63]

Constantinou, A., & Fenton, N. E. (2012). Solving the Problem of Inadequate Scoring Rules for Assessing Probabilistic Football Forecast Models. Journal of Quantitative Analysis in Sports, vol. 8, Iss. 1, Article 1. [DOI, draft].

 

Discussed in Jona's Opisthokonta blog

 

 
T [64]

Constantinou, A. (2009). Mathematical study of rational behaviour in Poker. MSc Thesis. Developed using C++. Department of Engineering and Information Sciences, University of Hertfordshire, UK, Supervised by Prof Daniel Polani. Grade: A.


T [65] Constantinou, A. (2008). Alpha-Beta in Computational Chess. BSc Final Year Project. Developed using C#. Department of Engineering and Information Sciences, University of Hertfordshire, UK. Supervised by Prof Daniel Polani. Grade: A.
    _____________________________________________________________________  
    published online, 19/02/2012
last updated, 07/06/2020
 
       
                       

                       
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