Giorgos Borboudakis

According to our database, Giorgos Borboudakis authored at least 20 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Confidence Interval Estimation of Predictive Performance in the Context of AutoML.

Konstantinos Paraschakis, Andrea Castellani, Giorgos Borboudakis, Ioannis Tsamardinos

CoRR, 2024

2023

A Meta-Level Learning Algorithm for Sequential Hyper-Parameter Space Reduction in AutoML.

Giorgos Borboudakis, Paulos Charonyktakis, Konstantinos Paraschakis, Ioannis Tsamardinos

CoRR, 2023

2021

Extending greedy feature selection algorithms to multiple solutions.

Giorgos Borboudakis, Ioannis Tsamardinos

Data Min. Knowl. Discov., 2021

2019

A greedy feature selection algorithm for Big Data of high dimensionality.

Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis, Polyvios Pratikakis, Vassilis Christophides

Mach. Learn., 2019

Forward-Backward Selection with Early Dropping.

Giorgos Borboudakis, Ioannis Tsamardinos

J. Mach. Learn. Res., 2019

2018

Efficient and accurate feature selection, with extensions for multiple solutions and to big data

Giorgos Borboudakis

PhD thesis, 2018

Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation.

Ioannis Tsamardinos, Elissavet Greasidou, Giorgos Borboudakis

Mach. Learn., 2018

Correction to: Constraint-based causal discovery with mixed data.

Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, Ioannis Tsamardinos

Int. J. Data Sci. Anal., 2018

Constraint-based causal discovery with mixed data.

Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, Ioannis Tsamardinos

Int. J. Data Sci. Anal., 2018

2017

Bootstrapping the Out-of-sample Predictions for Efficient and Accurate Cross-Validation.

Ioannis Tsamardinos, Elissavet Greasidou, Michalis Tsagris, Giorgos Borboudakis

CoRR, 2017

Massively-Parallel Feature Selection for Big Data.

Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis, Polyvios Pratikakis, Vassilis Christophides

CoRR, 2017

2016

Marginal Causal Consistency in Constraint-based Causal Learning.

Anna Roumpelaki, Giorgos Borboudakis, Sofia Triantafillou, Ioannis Tsamardinos

Proceedings of the UAI 2016 Workshop on Causation: Foundation to Application co-located with the 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), 2016

Towards Robust and Versatile Causal Discovery for Business Applications.

Giorgos Borboudakis, Ioannis Tsamardinos

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015

Bayesian Network Learning with Discrete Case-Control Data.

Giorgos Borboudakis, Ioannis Tsamardinos

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Addressing the data-association problem for multiple sound source localization using DOA estimates.

Anastasios Alexandridis, Giorgos Borboudakis, Athanasios Mouchtaris

Proceedings of the 23rd European Signal Processing Conference, 2015

2013

Scoring and Searching over Bayesian Networks with Causal and Associative Priors.

Giorgos Borboudakis, Ioannis Tsamardinos

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

2012

Scoring Bayesian Networks with Informative, Causal and Associative Priors

Giorgos Borboudakis, Ioannis Tsamardinos

CoRR, 2012

Incorporating Causal Prior Knowledge as Path-Constraints in Bayesian Networks and Maximal Ancestral Graphs.

Giorgos Borboudakis, Ioannis Tsamardinos

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

A constraint-based approach to incorporate prior knowledge in causal models.

Giorgos Borboudakis, Sofia Triantafilou, Vincenzo Lagani, Ioannis Tsamardinos

Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

2010

Permutation Testing Improves Bayesian Network Learning.

Ioannis Tsamardinos, Giorgos Borboudakis

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010