Permutation Testing Improves Bayesian Network Learning. - Ioannis Tsamardinos; Giorgos Borboudakis (ECML/PKDD (3), 2010)

A constraint-based approach to incorporate prior knowledge in causal models. - Giorgos Borboudakis; Sofia Triantafilou; Vincenzo Lagani; Ioannis Tsamardinos (ESANN, 2011)

Incorporating Causal Prior Knowledge as Path-Constraints in Bayesian Networks and Maximal Ancestral Graphs. - Giorgos Borboudakis; Ioannis Tsamardinos (ICML, 2012)

Scoring Bayesian Networks with Informative, Causal and Associative Priors - Giorgos Borboudakis; Ioannis Tsamardinos (CoRR, 2012)

Scoring and Searching over Bayesian Networks with Causal and Associative Priors. - Giorgos Borboudakis; Ioannis Tsamardinos (UAI, 2013)

Addressing the data-association problem for multiple sound source localization using DOA estimates. - Anastasios Alexandridis; Giorgos Borboudakis; Athanasios Mouchtaris (EUSIPCO, 2015)

Bayesian Network Learning with Discrete Case-Control Data. - Giorgos Borboudakis; Ioannis Tsamardinos (UAI, 2015)

Towards Robust and Versatile Causal Discovery for Business Applications. - Giorgos Borboudakis; Ioannis Tsamardinos (KDD, 2016)

Marginal Causal Consistency in Constraint-based Causal Learning. - Anna Roumpelaki; Giorgos Borboudakis; Sofia Triantafillou; Ioannis Tsamardinos (CFA@UAI, 2016)

Massively-Parallel Feature Selection for Big Data. - Ioannis Tsamardinos; Giorgos Borboudakis; Pavlos Katsogridakis; Polyvios Pratikakis; Vassilis Christophides (CoRR, 2017)

Bootstrapping the Out-of-sample Predictions for Efficient and Accurate Cross-Validation. - Ioannis Tsamardinos; Elissavet Greasidou; Michalis Tsagris; Giorgos Borboudakis (CoRR, 2017)

Constraint-based causal discovery with mixed data. - Michail Tsagris; Giorgos Borboudakis; Vincenzo Lagani; Ioannis Tsamardinos (Int. J. Data Sci. Anal., 2018)

Correction to: Constraint-based causal discovery with mixed data. - Michail Tsagris; Giorgos Borboudakis; Vincenzo Lagani; Ioannis Tsamardinos (Int. J. Data Sci. Anal., 2018)

Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation. - Ioannis Tsamardinos; Elissavet Greasidou; Giorgos Borboudakis (Mach. Learn., 2018)

Efficient and accurate feature selection, with extensions for multiple solutions and to big data - Giorgos Borboudakis (2018)

Forward-Backward Selection with Early Dropping. - Giorgos Borboudakis; Ioannis Tsamardinos (J. Mach. Learn. Res., 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)

Extending greedy feature selection algorithms to multiple solutions. - Giorgos Borboudakis; Ioannis Tsamardinos (Data Min. Knowl. Discov., 2021)

A Meta-Level Learning Algorithm for Sequential Hyper-Parameter Space Reduction in AutoML. - Giorgos Borboudakis; Paulos Charonyktakis; Konstantinos Paraschakis; Ioannis Tsamardinos (CoRR, 2023)

Confidence Interval Estimation of Predictive Performance in the Context of AutoML. - Konstantinos Paraschakis; Andrea Castellani; Giorgos Borboudakis; Ioannis Tsamardinos (AutoML, 2024)

CLBO: Conditional Local Bayesian Optimization for Automated Machine Learning. - George Paterakis; Giorgos Borboudakis; Konstantinos Paraschakis; Paulos Charonyktakis; Ioannis Tsamardinos (SETN, 2024)