Anthony C. Constantinou

Orcid: 0000-0001-7147-6821

According to our database1, Anthony C. Constantinou authored at least 45 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Tuning structure learning algorithms with out-of-sample and resampling strategies.
Knowl. Inf. Syst., August, 2024

The impact of variable ordering on Bayesian network structure learning.
Data Min. Knowl. Discov., July, 2024

Using GPT-4 to guide causal machine learning.
CoRR, 2024

Investigating potential causes of Sepsis with Bayesian network structure learning.
CoRR, 2024

Investigating the validity of structure learning algorithms in identifying risk factors for intervention in patients with diabetes.
CoRR, 2024

2023
Open problems in causal structure learning: A case study of COVID-19 in the UK.
Expert Syst. Appl., December, 2023

The impact of prior knowledge on causal structure learning.
Knowl. Inf. Syst., 2023

Hybrid Bayesian network discovery with latent variables by scoring multiple interventions.
Data Min. Knowl. Discov., 2023

Causal discovery using dynamically requested knowledge.
CoRR, 2023

A survey of Bayesian Network structure learning.
Artif. Intell. Rev., 2023

Improving the imputation of missing data with Markov Blanket discovery.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Greedy structure learning from data that contain systematic missing values.
Mach. Learn., 2022

Improving Bayesian Network Structure Learning in the Presence of Measurement Error.
J. Mach. Learn. Res., 2022

Effective and efficient structure learning with pruning and model averaging strategies.
Int. J. Approx. Reason., 2022

Parallel Sampling for Efficient High-dimensional Bayesian Network Structure Learning.
CoRR, 2022

Discovery and density estimation of latent confounders in Bayesian networks with evidence lower bound.
Proceedings of the International Conference on Probabilistic Graphical Models, 2022

2021
Learning Bayesian networks from demographic and health survey data.
J. Biomed. Informatics, 2021

Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data.
Int. J. Approx. Reason., 2021

The importance of temporal information in Bayesian network structure learning.
Expert Syst. Appl., 2021

Greedy structure learning from data that contains systematic missing values.
CoRR, 2021

Information fusion between knowledge and data in Bayesian network structure learning.
CoRR, 2021

How do some Bayesian Network machine learned graphs compare to causal knowledge?
CoRR, 2021

2020
Learning Bayesian Networks with the Saiyan Algorithm.
ACM Trans. Knowl. Discov. Data, 2020

Approximate Learning of High Dimensional Bayesian Network Structures via Pruning of Candidate Parent Sets.
Entropy, 2020

Asian Handicap football betting with Rating-based Hybrid Bayesian Networks.
CoRR, 2020

The Book of Why: The New Science of Cause and Effect, Judea Pearl, Dana Mackenzie. Basic Books (2018).
Artif. Intell., 2020

Learning Bayesian Networks That Enable Full Propagation of Evidence.
IEEE Access, 2020

Bayesian network structure learning with causal effects in the presence of latent variables.
Proceedings of the International Conference on Probabilistic Graphical Models, 2020

2019
Dolores: a model that predicts football match outcomes from all over the world.
Mach. Learn., 2019

Simpson's Paradox and the implications for medical trials.
CoRR, 2019

Evaluating structure learning algorithms with a balanced scoring function.
CoRR, 2019

2018
An improved method for solving Hybrid Influence Diagrams.
Int. J. Approx. Reason., 2018

Expected Value of Partial Perfect Information in Hybrid Models Using Dynamic Discretization.
IEEE Access, 2018

2017
Towards smart-data: Improving predictive accuracy in long-term football team performance.
Knowl. Based Syst., 2017

2016
How to model mutually exclusive events based on independent causal pathways in Bayesian network models.
Knowl. Based Syst., 2016

A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study.
Expert Syst. Appl., 2016

Integrating expert knowledge with data in Bayesian networks: Preserving data-driven expectations when the expert variables remain unobserved.
Expert Syst. Appl., 2016

Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences.
Artif. Intell. Medicine, 2016

From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support.
Artif. Intell. Medicine, 2016

Improving Predictive Accuracy Using Smart-Data rather than Big-Data: A Case Study of Soccer Teams' Evolving Performance.
Proceedings of the 13th UAI Bayesian Modeling Applications Workshop (BMAW 2016) co-located with the 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), 2016

2015
Risk assessment and risk management of violent reoffending among prisoners.
Expert Syst. Appl., 2015

Causal inference for violence risk management and decision support in forensic psychiatry.
Decis. Support Syst., 2015

2013
Bayesian networks for prediction, risk assessment and decision making in an inefficient Association Football gambling market.
PhD thesis, 2013

Profiting from an inefficient association football gambling market: Prediction, risk and uncertainty using Bayesian networks.
Knowl. Based Syst., 2013

2012
pi-football: A Bayesian network model for forecasting Association Football match outcomes.
Knowl. Based Syst., 2012


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