| Chemically intuited, large-scale screening of MOFs by machine learning techniques G Borboudakis, T Stergiannakos, M Frysali, E Klontzas, I Tsamardinos, ... Nature Partner Journals Computational Materials 3 (1), 40, 2017 | 70 | 2017 |
| Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation I Tsamardinos, E Greasidou, G Borboudakis Machine Learning 107 (12), 1895–1922, 2018 | 54 | 2018 |
| Permutation testing improves Bayesian network learning I Tsamardinos, G Borboudakis European Conference on Machine Learning and Principles and Practice of …, 2010 | 46 | 2010 |
| Forward-Backward Selection with Early Dropping G Borboudakis, I Tsamardinos Journal of Machine Learning Research 20 (8), 1-39, 2019 | 37 | 2019 |
| Incorporating causal prior knowledge as path-constraints in Bayesian networks and maximal ancestral graphs G Borboudakis, I Tsamardinos 29th International Conference on Machine Learning (ICML 2012), 2012 | 27 | 2012 |
| A greedy feature selection algorithm for Big Data of high dimensionality I Tsamardinos, G Borboudakis, P Katsogridakis, P Pratikakis, ... Machine learning 108 (2), 149-202, 2018 | 24 | 2018 |
| Rfast: A collection of efficient and extremely fast R functions M Papadakis, M Tsagris, M Dimitriadis, S Fafalios, I Tsamardinos, ... R package version 1 (2), 2018 | 19 | 2018 |
| Constraint-based Causal Discovery with Mixed Data M Tsagris, G Borboudakis, V Lagani, I Tsamardinos International Journal of Data Science and Analytics, 2018 | 19 | 2018 |
| Towards Robust and Versatile Causal Discovery for Business Applications. G Borboudakis, I Tsamardinos 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016 …, 2016 | 19* | 2016 |
| Just add data: automated predictive modeling and biosignature discovery I Tsamardinos, P Charonyktakis, K Lakiotaki, G Borboudakis, ... Biorxiv, 2020 | 12 | 2020 |
| A constraint-based approach to incorporate prior knowledge in causal models. G Borboudakis, S Triantafilou, V Lagani, I Tsamardinos 19th European Symposium on Artificial Neural Networks (ESANN 2011), 2011 | 11 | 2011 |
| Marginal Causal Consistency in Constraint-based Causal Learning. A Roumpelaki, G Borboudakis, S Triantafillou, I Tsamardinos Causation: Foundation to Application Workshop (UAI 2016), 39-47, 2016 | 10* | 2016 |
| Addressing the data-association problem for multiple sound source localization using doa estimates A Alexandridis, G Borboudakis, A Mouchtaris 23rd European Signal Processing Conference (EUSIPCO 2015), 1551-1555, 2015 | 9 | 2015 |
| Scoring and Searching over Bayesian Networks with Causal and Associative Priors G Borboudakis, I Tsamardinos 29th Conference on Uncertainty in Artificial Intelligence (UAI 2013), 2013 | 8* | 2013 |
| Bayesian Network Learning with Discrete Case-Control Data. G Borboudakis, I Tsamardinos 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), 151-160, 2015 | 7 | 2015 |
| Tools and Algorithms for Causally Interpreting Directed Edges in Maximal Ancestral Graphs G Borboudakis, S Triantafillou, I Tsamardinos The Sixth European Workshop on Probabilistic Graphical Models (PGM 2012), 2012 | 6 | 2012 |
| A data driven approach reveals disease similarity on a molecular level K Lakiotaki, G Georgakopoulos, E Castanas, OD Rĝe, G Borboudakis, ... Nature Partner Journals Systems Biology and Applications 5 (1), 1-10, 2019 | 3 | 2019 |
| Chemosensitivity Prediction of Tumours Based on Expression, miRNA, and Proteomics Data I Tsamardinos, G Borboudakis, EG Christodoulou, OD Rĝe International Journal of Systems Biology and Biomedical Technologies (IJSBBT …, 2012 | 1 | 2012 |
| Efficient and Accurate Feature Selection, with Extensions for Multiple Solutions and to Big Data G Borboudakis University of Crete - Computer Science Department, 2018 | | 2018 |
| Package ‘MXM’ I Tsamardinos, V Lagani, G Athineou, M Tsagris, G Borboudakis, ... | | 2017 |
Ioannis TsamardinosProfessor, Computer Science Department, University of CreteVerified email at csd.uoc.gr
