Ioannis Tsamardinos

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 50

Top Venues

Publications

Konstantinos Paraschakis, Andrea Castellani, Giorgos Borboudakis, Ioannis Tsamardinos
Confidence Interval Estimation of Predictive Performance in the Context of AutoML. CoRR (2024)
Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
AutoML for Explainable Anomaly Detection (XAD). Tannen's Festschrift (2024)
Konstantina Biza, Antonios Ntroumpogiannis, Sofia Triantafillou, Ioannis Tsamardinos
Towards Automated Causal Discovery: a case study on 5G telecommunication data. CoRR (2024)
Konstantina Biza, Ioannis Tsamardinos, Sofia Triantafillou
Out-of-Sample Tuning for Causal Discovery. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
George Paterakis, Stefanos Fafalios, Paulos Charonyktakis, Vassilis Christophides, Ioannis Tsamardinos
Do We Really Need Imputation in AutoML Predictive Modeling? ACM Trans. Knowl. Discov. Data 18 (6) (2024)
Giorgos Borboudakis, Paulos Charonyktakis, Konstantinos Paraschakis, Ioannis Tsamardinos
A Meta-Level Learning Algorithm for Sequential Hyper-Parameter Space Reduction in AutoML. CoRR (2023)
Ioulia Karagiannaki, Krystallia Gourlia, Vincenzo Lagani, Yannis Pantazis, Ioannis Tsamardinos
Learning biologically-interpretable latent representations for gene expression data. Mach. Learn. 112 (11) (2023)
Kleanthi Lakiotaki, Zacharias Papadovasilakis, Vincenzo Lagani, Stefanos Fafalios, Paulos Charonyktakis, Michail Tsagris, Ioannis Tsamardinos
Automated machine learning for genome wide association studies. Bioinform. 39 (9) (2023)
Antonios Ntroumpogiannis, Michail Giannoulis, Nikolaos Myrtakis, Vassilis Christophides, Eric Simon, Ioannis Tsamardinos
A meta-level analysis of online anomaly detectors. VLDB J. 32 (4) (2023)
Michail Tsagris, Zacharias Papadovasilakis, Kleanthi Lakiotaki, Ioannis Tsamardinos
The $\gamma$γ-OMP Algorithm for Feature Selection With Application to Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 19 (2) (2022)
Vasilios Plakandaras, Periklis Gogas, Theophilos Papadimitriou, Ioannis Tsamardinos
Credit Card Fraud Detection with Automated Machine Learning Systems. Appl. Artif. Intell. 36 (1) (2022)
Antonios Ntroumpogiannis, Michail Giannoulis, Nikolaos Myrtakis, Vassilis Christophides, Eric Simon, Ioannis Tsamardinos
A Meta-level Analysis of Online Anomaly Detectors. CoRR (2022)
Ioannis Tsamardinos
Don't lose samples to estimation. Patterns 3 (12) (2022)
Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
PROTEUS: Predictive Explanation of Anomalies. ICDE (2021)
Giorgos Borboudakis, Ioannis Tsamardinos
Extending greedy feature selection algorithms to multiple solutions. Data Min. Knowl. Discov. 35 (4) (2021)
Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
On Predictive Explanation of Data Anomalies. CoRR (2021)
Maria Papadogiorgaki, Maria Venianaki, Paulos Charonyktakis, Marios Antonakakis, Ioannis Tsamardinos, Michalis E. Zervakis, Vangelis Sakkalis
Heart Rate Classification Using ECG Signal Processing and Machine Learning Methods. BIBE (2021)
Iordanis Xanthopoulos, Ioannis Tsamardinos, Vassilis Christophides, Eric Simon, Alejandro Salinger
Putting the Human Back in the AutoML Loop. EDBT/ICDT Workshops (2020)
Michail Tsagris, Zacharias Papadovasilakis, Kleanthi Lakiotaki, Ioannis Tsamardinos
A generalised OMP algorithm for feature selection with application to gene expression data. CoRR (2020)
Konstantina Biza, Ioannis Tsamardinos, Sofia Triantafillou
Tuning Causal Discovery Algorithms. PGM (2020)
Anastasios Tsourtis, Yannis Pantazis, Ioannis Tsamardinos
Inference of Stochastic Dynamical Systems from Cross-Sectional Population Data. CoRR (2020)
Yannis Pantazis, Christos Tselas, Kleanthi Lakiotaki, Vincenzo Lagani, Ioannis Tsamardinos
Latent Feature Representations for Human Gene Expression Data Improve Phenotypic Predictions. BIBM (2020)
Ioulia Karagiannaki, Yannis Pantazis, Ekaterini Chatzaki, Ioannis Tsamardinos
Pathway Activity Score Learning for Dimensionality Reduction of Gene Expression Data. DS (2020)
Giorgos Borboudakis, Ioannis Tsamardinos
Forward-Backward Selection with Early Dropping. J. Mach. Learn. Res. 20 (2019)
Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis, Polyvios Pratikakis, Vassilis Christophides
A greedy feature selection algorithm for Big Data of high dimensionality. Mach. Learn. 108 (2) (2019)
Yannis Pantazis, Ioannis Tsamardinos
A unified approach for sparse dynamical system inference from temporal measurements. Bioinform. 35 (18) (2019)
Ioannis Tsamardinos, Elissavet Greasidou, Giorgos Borboudakis
Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation. Mach. Learn. 107 (12) (2018)
Marios Adamou, Grigoris Antoniou, Elissavet Greasidou, Vincenzo Lagani, Paulos Charonyktakis, Ioannis Tsamardinos
Mining Free-Text Medical Notes for Suicide Risk Assessment. SETN (2018)
Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, Ioannis Tsamardinos
Correction to: Constraint-based causal discovery with mixed data. Int. J. Data Sci. Anal. 6 (1) (2018)
Michail Tsagris, Ioannis Tsamardinos
. F1000Research 7 (2018)
Kleanthi Lakiotaki, Nikolaos Vorniotakis, Michail Tsagris, Georgios Georgakopoulos, Ioannis Tsamardinos
BioDataome: a collection of uniformly preprocessed and automatically annotated datasets for data-driven biology. Database J. Biol. Databases Curation 2018 (2018)
Michail Tsagris, Vincenzo Lagani, Ioannis Tsamardinos
Feature selection for high-dimensional temporal data. BMC Bioinform. 19 (1) (2018)
Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, Ioannis Tsamardinos
Constraint-based causal discovery with mixed data. Int. J. Data Sci. Anal. 6 (1) (2018)
Konstantinos Tsirlis, Vincenzo Lagani, Sofia Triantafillou, Ioannis Tsamardinos
On scoring Maximal Ancestral Graphs with the Max-Min Hill Climbing algorithm. Int. J. Approx. Reason. 102 (2018)
Giorgos Papoutsoglou, Giorgos Athineou, Vincenzo Lagani, Iordanis Xanthopoulos, Angelika Schmidt, Szabolcs Elias, Jesper Tegnér, Ioannis Tsamardinos
SCENERY: a web application for (causal) network reconstruction from cytometry data. Nucleic Acids Res. 45 (Webserver-Issue) (2017)
Ioannis Tsamardinos, Elissavet Greasidou, Michalis Tsagris, Giorgos Borboudakis
Bootstrapping the Out-of-sample Predictions for Efficient and Accurate Cross-Validation. CoRR (2017)
Giorgos Borboudakis, Ioannis Tsamardinos
Forward-Backward Selection with Early Dropping. CoRR (2017)
Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis, Polyvios Pratikakis, Vassilis Christophides
Massively-Parallel Feature Selection for Big Data. CoRR (2017)
Sofia Triantafillou, Ioannis Tsamardinos
Score-based vs Constraint-based Causal Learning in the Presence of Confounders. CFA@UAI (2016)
Giorgos Athineou, Giorgos Papoutsoglou, Sofia Triantafillou, Ioannis Basdekis, Vincenzo Lagani, Ioannis Tsamardinos
SCENERY: A Web-Based Application for Network Reconstruction and Visualization of Cytometry Data. PACBB (2016)
Paulos Charonyktakis, Maria Plakia, Ioannis Tsamardinos, Maria Papadopouli
On User-Centric Modular QoE Prediction for VoIP Based on Machine-Learning Algorithms. IEEE Trans. Mob. Comput. 15 (6) (2016)
Giorgos Borboudakis, Ioannis Tsamardinos
Towards Robust and Versatile Causal Discovery for Business Applications. KDD (2016)
Anna Roumpelaki, Giorgos Borboudakis, Sofia Triantafillou, Ioannis Tsamardinos
Marginal Causal Consistency in Constraint-based Causal Learning. CFA@UAI (2016)
Vincenzo Lagani, Argyro D. Karozou, David Gomez-Cabrero, Gilad Silberberg, Ioannis Tsamardinos
Erratum to: A comparative evaluation of data-merging and meta-analysis methods for reconstructing gene-gene interactions. BMC Bioinform. 17 (2016)
Vincenzo Lagani, Argyro D. Karozou, David Gomez-Cabrero, Gilad Silberberg, Ioannis Tsamardinos
A comparative evaluation of data-merging and meta-analysis methods for reconstructing gene-gene interactions. BMC Bioinform. 17 (S-5) (2016)
Giorgos Borboudakis, Ioannis Tsamardinos
Bayesian Network Learning with Discrete Case-Control Data. UAI (2015)
Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos
Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning. KDD (2015)
Ioannis Tsamardinos, Amin Rakhshani, Vincenzo Lagani
Performance-Estimation Properties of Cross-Validation-Based Protocols with Simultaneous Hyper-Parameter Optimization. Int. J. Artif. Intell. Tools 24 (5) (2015)
Grace T. Huang, Ioannis Tsamardinos, Vineet K. Raghu, Naftali Kaminski, Panayiotis V. Benos
T-ReCS: Stable Selection of Dynamically Formed Groups of Features with Application to Prediction of Clinical Outcomes. Pacific Symposium on Biocomputing (2015)
Sofia Triantafillou, Ioannis Tsamardinos
Constraint-based causal discovery from multiple interventions over overlapping variable sets. J. Mach. Learn. Res. 16 (2015)
Sofia Triantafilou, Ioannis Tsamardinos, Anna Roumpelaki
Learning Neighborhoods of High Confidence in Constraint-Based Causal Discovery. Probabilistic Graphical Models (2014)
Giorgos Borboudakis, Ioannis Tsamardinos
Scoring and Searching over Bayesian Networks with Causal and Associative Priors. CoRR (2014)
Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos
Discovering and Exploiting Entailment Relationships in Multi-Label Learning. CoRR (2014)
Nestoras Karathanasis, Ioannis Tsamardinos, Panayiota Poirazi
Don't use a cannon to kill the ... miRNA mosquito. Bioinform. 30 (7) (2014)
Sofia Triantafilou, Ioannis Tsamardinos
Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets. CoRR (2014)
Ioannis Tsamardinos, Amin Rakhshani, Vincenzo Lagani
Performance-Estimation Properties of Cross-Validation-Based Protocols with Simultaneous Hyper-Parameter Optimization. SETN (2014)
Nestoras Karathanasis, Ioannis Tsamardinos, Panayiota Poirazi
A bioinformatics approach for investigating the determinants of Drosha processing. BIBE (2013)
Giorgos Borboudakis, Ioannis Tsamardinos
Scoring and Searching over Bayesian Networks with Causal and Associative Priors. UAI (2013)
Laura E. Brown, Ioannis Tsamardinos, Douglas P. Hardin
To feature space and back: Identifying top-weighted features in polynomial Support Vector Machine models. Intell. Data Anal. 16 (4) (2012)
Nestoras Karathanasis, Ioannis Tsamardinos, Angelos P. Armen, Panayiota Poirazi
SVM-based miRNA: MiRNA∗ duplex prediction. BIBE (2012)
Giorgos Borboudakis, Ioannis Tsamardinos
Scoring Bayesian Networks with Informative, Causal and Associative Priors CoRR (2012)
Giorgos Borboudakis, Ioannis Tsamardinos
Incorporating Causal Prior Knowledge as Path-Constraints in Bayesian Networks and Maximal Ancestral Graphs. ICML (2012)
Vincenzo Lagani, Ioannis Tsamardinos, Sofia Triantafilou
Learning from Mixture of Experimental Data: A Constraint-Based Approach. SETN (2012)
Ioannis Tsamardinos, Sofia Triantafilou, Vincenzo Lagani
Towards Integrative Causal Analysis of Heterogeneous Data Sets and Studies. J. Mach. Learn. Res. 13 (2012)
Sophia Kleisarchaki, Dimitris Kotzinos, Ioannis Tsamardinos, Vassilis Christophides
A Methodological Framework for Statistical Analysis of Social Text Streams. ISIP (2012)
Angelos P. Armen, Ioannis Tsamardinos
A unified approach to estimation and control of the False Discovery Rate in Bayesian network skeleton identification. ESANN (2011)
Lefteris Koumakis, Franco Chiarugi, Vincenzo Lagani, Angelina Kouroubali, Ioannis Tsamardinos
Risk Assessment Models for Diabetes Complications: A Survey of Available Online Tools. MobiHealth (2011)
Giorgos Borboudakis, Sofia Triantafilou, Vincenzo Lagani, Ioannis Tsamardinos
A constraint-based approach to incorporate prior knowledge in causal models. ESANN (2011)
Chrysi Filippaki, Grigoris Antoniou, Ioannis Tsamardinos
Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition. AmI (2011)
Eleni G. Christodoulou, O. D. Røe, Amos Folarin, Ioannis Tsamardinos
Information-Preserving Techniques Improve Chemosensitivity Prediction of Tumours Based on Expression Profiles. EANN/AIAI (1) (2011)
Ioannis Tsamardinos, Giorgos Borboudakis
Permutation Testing Improves Bayesian Network Learning. ECML/PKDD (3) (2010)
Sofia Triantafilou, Ioannis Tsamardinos, Ioannis G. Tollis
Learning Causal Structure from Overlapping Variable Sets. AISTATS (2010)
Vincenzo Lagani, Ioannis Tsamardinos
Structure-based variable selection for survival data. Bioinform. 26 (15) (2010)
Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions. J. Mach. Learn. Res. 11 (2010)
Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation. J. Mach. Learn. Res. 11 (2010)
Ioannis Tsamardinos, Asimakis P. Mariglis
Multi-Source Causal Analysis: Learning Bayesian Networks from Multiple Datasets. AIAI (2009)
Ioannis Tsamardinos, Laura E. Brown
Bounding the False Discovery Rate in Local Bayesian Network Learning. AAAI (2008)
Laura E. Brown, Ioannis Tsamardinos
A Strategy for Making Predictions Under Manipulation. WCCI Causation and Prediction Challenge (2008)
Ioannis Tsamardinos
Causal Data Mining in Bioinformatics. ERCIM News 2007 (69) (2007)
Ioannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis
The max-min hill-climbing Bayesian network structure learning algorithm. Mach. Learn. 65 (1) (2006)
Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown, Constantin F. Aliferis
Generating Realistic Large Bayesian Networks by Tiling. FLAIRS Conference (2006)
Yindalon Aphinyanaphongs, Ioannis Tsamardinos, Alexander R. Statnikov, Douglas P. Hardin, Constantin F. Aliferis
Research Paper: Text Categorization Models for High-Quality Article Retrieval in Internal Medicine. J. Am. Medical Informatics Assoc. 12 (2) (2005)
Alexander R. Statnikov, Ioannis Tsamardinos, Yerbolat Dosbayev, Constantin F. Aliferis
GEMS: A system for automated cancer diagnosis and biomarker discovery from microarray gene expression data. Int. J. Medical Informatics 74 (7-8) (2005)
Alexander R. Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos, Douglas P. Hardin, Shawn Levy
A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis. Bioinform. 21 (5) (2005)
Lawrence D. Fu, Ioannis Tsamardinos
A Comparison of Bayesian Network Learning Algorithms from Continuous Data. AMIA (2005)
Alexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis
Using the GEMS System for Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data. AAAI (2005)
Alexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis
System for Supervised Analysis of Cancer Microarray Gene Expression Data. AMIA (2005)
Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms. AAAI (2005)
Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
A Novel Algorithm for Scalable and Accurate Bayesian Network Learning. MedInfo (2004)
Douglas P. Hardin, Ioannis Tsamardinos, Constantin F. Aliferis
A theoretical characterization of linear SVM-based feature selection. ICML (2004)
Alexander R. Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos
Methods for Multi-Category Cancer Diagnosis from Gene Expression Data: A Comprehensive Evaluation to Inform Decision Support System Development. MedInfo (2004)
Constantin F. Aliferis, Ioannis Tsamardinos, Pierre P. Massion, Alexander R. Statnikov, Nafeh Fananapazir, Douglas P. Hardin
Machine Learning Models for Classification of Lung Cancer and Selection of Genomic Markers Using Array Gene Expression Data. FLAIRS Conference (2003)
Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
Time and sample efficient discovery of Markov blankets and direct causal relations. KDD (2003)
Lewis J. Frey, Douglas H. Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
Identifying Markov Blankets with Decision Tree Induction. ICDM (2003)
Martha E. Pollack, Laura E. Brown, Dirk Colbry, Colleen E. McCarthy, Cheryl Orosz, Bart Peintner, Sailesh Ramakrishnan, Ioannis Tsamardinos
Autominder: an intelligent cognitive orthotic system for people with memory impairment. Robotics Auton. Syst. 44 (3-4) (2003)
Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
Algorithms for Large Scale Markov Blanket Discovery. FLAIRS Conference (2003)
Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery. METMBS (2003)
Constantin F. Aliferis, Ioannis Tsamardinos, Pierre P. Massion, Alexander R. Statnikov, Douglas P. Hardin
Why Classification Models Using Array Gene Expression Data Perform So Well: A Preliminary Investigation of Explanatory Factors. METMBS (2003)
Ioannis Tsamardinos, Martha E. Pollack
Efficient solution techniques for disjunctive temporal reasoning problems. Artif. Intell. 151 (1-2) (2003)
Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov
HITON: A Novel Markov Blanket Algorithm for Optimal Variable Selection. AMIA (2003)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ioannis Tsamardinos