Tsamardinos, Ioannis

25 publications

NeurIPS 2024 ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions Etienne Vareille, Michele Linardi, Ioannis Tsamardinos, Vassilis Christophides

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

MLJ 2023 Learning Biologically-Interpretable Latent Representations for Gene Expression Data Ioulia Karagiannaki, Krystallia Gourlia, Vincenzo Lagani, Yannis Pantazis, Ioannis Tsamardinos

PGM 2020 Tuning Causal Discovery Algorithms Konstantina Biza, Ioannis Tsamardinos, Sofia Triantafillou

MLJ 2019 A Greedy Feature Selection Algorithm for Big Data of High Dimensionality Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis, Polyvios Pratikakis, Vassilis Christophides

JMLR 2019 Forward-Backward Selection with Early Dropping Giorgos Borboudakis, Ioannis Tsamardinos

MLJ 2018 Bootstrapping the Out-of-Sample Predictions for Efficient and Accurate Cross-Validation Ioannis Tsamardinos, Elissavet Greasidou, Giorgos Borboudakis

UAI 2016 Marginal Causal Consistency in Constraint-Based Causal Learning Anna Roumpelaki, Giorgos Borboudakis, Sofia Triantafillou, Ioannis Tsamardinos

UAI 2016 Score-Based vs Constraint-Based Causal Learning in the Presence of Confounders Sofia Triantafillou, Ioannis Tsamardinos

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

JMLR 2015 Constraint-Based Causal Discovery from Multiple Interventions over Overlapping Variable Sets Sofia Triantafillou, Ioannis Tsamardinos

UAI 2013 Scoring and Searching over Bayesian Networks with Causal and Associative Priors Giorgos Borboudakis, Ioannis Tsamardinos

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

JMLR 2012 Towards Integrative Causal Analysis of Heterogeneous Data Sets and Studies Ioannis Tsamardinos, Sofia Triantafillou, Vincenzo Lagani

AISTATS 2010 Learning Causal Structure from Overlapping Variable Sets Sofia Triantafillou, Ioannis Tsamardinos, Ioannis Tollis

JMLR 2010 Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos

JMLR 2010 Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos

ECML-PKDD 2010 Permutation Testing Improves Bayesian Network Learning Ioannis Tsamardinos, Giorgos Borboudakis

AAAI 2008 Bounding the False Discovery Rate in Local Bayesian Network Learning Ioannis Tsamardinos, Laura E. Brown

MLJ 2006 The Max-Min Hill-Climbing Bayesian Network Structure Learning Algorithm Ioannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis

AAAI 2005 A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis

AAAI 2005 Using the GEMS System for Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data Alexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis

ICML 2004 A Theoretical Characterization of Linear SVM-Based Feature Selection Douglas P. Hardin, Ioannis Tsamardinos, Constantin F. Aliferis

AISTATS 2003 Towards Principled Feature Selection: Relevancy, Filters and Wrappers Ioannis Tsamardinos, Constantin F. Aliferis

AAAI 1998 Fast Transformation of Temporal Plans for Efficient Execution Ioannis Tsamardinos, Nicola Muscettola, Paul H. Morris