Ioannis Tsamardinos

120 papers A* 12A 4B 3C 4Misc 9Journal 59Unranked 29

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Large Causal Models for Temporal Causal Discovery. CoRR Nikolaos Kougioulis, Nikolaos Gkorgkolis, MingXue Wang, Bora Caglayan, Dario Simionato, Andrea Tonon, Ioannis Tsamardinos
2025	J	`jnl`	A Comparative Analysis of Influence Signals for Data Debugging. CoRR Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
2025	J	`jnl`	A Comprehensive Perspective on Explainable AI across the Machine Learning Workflow. CoRR George Paterakis, Andrea Castellani, George Papoutsoglou, Tobias Rodemann, Ioannis Tsamardinos
2025	—	`conf`	Data Glitches Discovery using Influence-based Model Explanations. KDD (1) Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
2025	J	`jnl`	Predicting and Explaining Traffic Crash Severity Through Crash Feature Selection. CoRR Andrea Castellani, Zacharias Papadovasilakis, Giorgos Papoutsoglou, Mary Cole, Brian Bautsch, Tobias Rodemann, Ioannis Tsamardinos, Angela Harden
2025	J	`jnl`	Temporal Causal-based Simulation for Realistic Time-series Generation. CoRR Nikolaos Gkorgkolis, Nikolaos Kougioulis, MingXue Wang, Bora Caglayan, Andrea Tonon, Dario Simionato, Ioannis Tsamardinos
2024	—	`conf`	AI-Based Suicide Risk Assessment. IISA Pavlos Charonyktakis, Grigoris Antoniou, Marios Adamou, Michael Doyle, Sotiris Batsakis, Ioannis Tsamardinos
2024	—	`conf`	AutoML for Explainable Anomaly Detection (XAD). Tannen's Festschrift Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
2024	—	`conf`	CLBO: Conditional Local Bayesian Optimization for Automated Machine Learning. SETN George Paterakis, Giorgos Borboudakis, Konstantinos Paraschakis, Paulos Charonyktakis, Ioannis Tsamardinos
2024	A*	`conf`	ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions. NeurIPS Etienne Vareille, Michele Linardi, Ioannis Tsamardinos, Vassilis Christophides
2024	—	`conf`	Confidence Interval Estimation of Predictive Performance in the Context of AutoML. AutoML Konstantinos Paraschakis, Andrea Castellani, Giorgos Borboudakis, Ioannis Tsamardinos
2024	J	`jnl`	Confidence Interval Estimation of Predictive Performance in the Context of AutoML. CoRR Konstantinos Paraschakis, Andrea Castellani, Giorgos Borboudakis, Ioannis Tsamardinos
2024	J	`jnl`	Do We Really Need Imputation in AutoML Predictive Modeling? ACM Trans. Knowl. Discov. Data George Paterakis, Stefanos Fafalios, Paulos Charonyktakis, Vassilis Christophides, Ioannis Tsamardinos
2024	—	`conf`	ETIA: Towards an Automated Causal Discovery Pipeline. DS (2) Konstantina Biza, Antonios Ntroumpogiannis, Sofia Triantafillou, Ioannis Tsamardinos
2024	J	`jnl`	Out-of-Sample Tuning for Causal Discovery. IEEE Trans. Neural Networks Learn. Syst. Konstantina Biza, Ioannis Tsamardinos, Sofia Triantafillou
2024	J	`jnl`	Towards Automated Causal Discovery: a case study on 5G telecommunication data. CoRR Konstantina Biza, Antonios Ntroumpogiannis, Sofia Triantafillou, Ioannis Tsamardinos
2023	J	`jnl`	A Meta-Level Learning Algorithm for Sequential Hyper-Parameter Space Reduction in AutoML. CoRR Giorgos Borboudakis, Paulos Charonyktakis, Konstantinos Paraschakis, Ioannis Tsamardinos
2023	J	`jnl`	A meta-level analysis of online anomaly detectors. VLDB J. Antonios Ntroumpogiannis, Michail Giannoulis, Nikolaos Myrtakis, Vassilis Christophides, Eric Simon, Ioannis Tsamardinos
2023	J	`jnl`	Automated machine learning for genome wide association studies. Bioinform. Kleanthi Lakiotaki, Zacharias Papadovasilakis, Vincenzo Lagani, Stefanos Fafalios, Paulos Charonyktakis, Michail Tsagris, Ioannis Tsamardinos
2023	J	`jnl`	Learning biologically-interpretable latent representations for gene expression data. Mach. Learn. Ioulia Karagiannaki, Krystallia Gourlia, Vincenzo Lagani, Yannis Pantazis, Ioannis Tsamardinos
2022	J	`jnl`	A Meta-level Analysis of Online Anomaly Detectors. CoRR Antonios Ntroumpogiannis, Michail Giannoulis, Nikolaos Myrtakis, Vassilis Christophides, Eric Simon, Ioannis Tsamardinos
2022	J	`jnl`	Credit Card Fraud Detection with Automated Machine Learning Systems. Appl. Artif. Intell. Vasilios Plakandaras, Periklis Gogas, Theophilos Papadimitriou, Ioannis Tsamardinos
2022	J	`jnl`	Don't lose samples to estimation. Patterns Ioannis Tsamardinos
2022	J	`jnl`	The $\gamma$γ-OMP Algorithm for Feature Selection With Application to Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. Michail Tsagris, Zacharias Papadovasilakis, Kleanthi Lakiotaki, Ioannis Tsamardinos
2021	J	`jnl`	Extending greedy feature selection algorithms to multiple solutions. Data Min. Knowl. Discov. Giorgos Borboudakis, Ioannis Tsamardinos
2021	C	`conf`	Heart Rate Classification Using ECG Signal Processing and Machine Learning Methods. BIBE Maria Papadogiorgaki, Maria Venianaki, Paulos Charonyktakis, Marios Antonakakis, Ioannis Tsamardinos, Michalis E. Zervakis, Vangelis Sakkalis
2021	J	`jnl`	On Predictive Explanation of Data Anomalies. CoRR Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
2021	A*	`conf`	PROTEUS: Predictive Explanation of Anomalies. ICDE Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
2020	J	`jnl`	A generalised OMP algorithm for feature selection with application to gene expression data. CoRR Michail Tsagris, Zacharias Papadovasilakis, Kleanthi Lakiotaki, Ioannis Tsamardinos
2020	J	`jnl`	Inference of Stochastic Dynamical Systems from Cross-Sectional Population Data. CoRR Anastasios Tsourtis, Yannis Pantazis, Ioannis Tsamardinos
2020	—	`conf`	Latent Feature Representations for Human Gene Expression Data Improve Phenotypic Predictions. BIBM Yannis Pantazis, Christos Tselas, Kleanthi Lakiotaki, Vincenzo Lagani, Ioannis Tsamardinos
2020	B	`conf`	Pathway Activity Score Learning for Dimensionality Reduction of Gene Expression Data. DS Ioulia Karagiannaki, Yannis Pantazis, Ekaterini Chatzaki, Ioannis Tsamardinos
2020	—	`conf`	Putting the Human Back in the AutoML Loop. EDBT/ICDT Workshops Iordanis Xanthopoulos, Ioannis Tsamardinos, Vassilis Christophides, Eric Simon, Alejandro Salinger
2020	—	`conf`	Tuning Causal Discovery Algorithms. PGM Konstantina Biza, Ioannis Tsamardinos, Sofia Triantafillou
2019	J	`jnl`	A greedy feature selection algorithm for Big Data of high dimensionality. Mach. Learn. Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis, Polyvios Pratikakis, Vassilis Christophides
2019	J	`jnl`	A unified approach for sparse dynamical system inference from temporal measurements. Bioinform. Yannis Pantazis, Ioannis Tsamardinos
2019	J	`jnl`	Forward-Backward Selection with Early Dropping. J. Mach. Learn. Res. Giorgos Borboudakis, Ioannis Tsamardinos
2018	J	`jnl`	BioDataome: a collection of uniformly preprocessed and automatically annotated datasets for data-driven biology. Database J. Biol. Databases Curation Kleanthi Lakiotaki, Nikolaos Vorniotakis, Michail Tsagris, Georgios Georgakopoulos, Ioannis Tsamardinos
2018	J	`jnl`	Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation. Mach. Learn. Ioannis Tsamardinos, Elissavet Greasidou, Giorgos Borboudakis
2018	J	`jnl`	Constraint-based causal discovery with mixed data. Int. J. Data Sci. Anal. Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, Ioannis Tsamardinos
2018	J	`jnl`	Correction to: Constraint-based causal discovery with mixed data. Int. J. Data Sci. Anal. Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, Ioannis Tsamardinos
2018	J	`jnl`	Feature selection for high-dimensional temporal data. BMC Bioinform. Michail Tsagris, Vincenzo Lagani, Ioannis Tsamardinos
2018	J	`jnl`	Feature selection with the R package F1000Research Michail Tsagris, Ioannis Tsamardinos
2018	—	`conf`	Mining Free-Text Medical Notes for Suicide Risk Assessment. SETN Marios Adamou, Grigoris Antoniou, Elissavet Greasidou, Vincenzo Lagani, Paulos Charonyktakis, Ioannis Tsamardinos
2018	J	`jnl`	On scoring Maximal Ancestral Graphs with the Max-Min Hill Climbing algorithm. Int. J. Approx. Reason. Konstantinos Tsirlis, Vincenzo Lagani, Sofia Triantafillou, Ioannis Tsamardinos
2017	J	`jnl`	Bootstrapping the Out-of-sample Predictions for Efficient and Accurate Cross-Validation. CoRR Ioannis Tsamardinos, Elissavet Greasidou, Michalis Tsagris, Giorgos Borboudakis
2017	J	`jnl`	Forward-Backward Selection with Early Dropping. CoRR Giorgos Borboudakis, Ioannis Tsamardinos
2017	J	`jnl`	Massively-Parallel Feature Selection for Big Data. CoRR Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis, Polyvios Pratikakis, Vassilis Christophides
2017	J	`jnl`	SCENERY: a web application for (causal) network reconstruction from cytometry data. Nucleic Acids Res. Giorgos Papoutsoglou, Giorgos Athineou, Vincenzo Lagani, Iordanis Xanthopoulos, Angelika Schmidt, Szabolcs Elias, Jesper Tegnér, Ioannis Tsamardinos
2016	J	`jnl`	A comparative evaluation of data-merging and meta-analysis methods for reconstructing gene-gene interactions. BMC Bioinform. Vincenzo Lagani, Argyro D. Karozou, David Gomez-Cabrero, Gilad Silberberg, Ioannis Tsamardinos
2016	J	`jnl`	Erratum to: A comparative evaluation of data-merging and meta-analysis methods for reconstructing gene-gene interactions. BMC Bioinform. Vincenzo Lagani, Argyro D. Karozou, David Gomez-Cabrero, Gilad Silberberg, Ioannis Tsamardinos
2016	—	`conf`	Marginal Causal Consistency in Constraint-based Causal Learning. CFA@UAI Anna Roumpelaki, Giorgos Borboudakis, Sofia Triantafillou, Ioannis Tsamardinos
2016	J	`jnl`	On User-Centric Modular QoE Prediction for VoIP Based on Machine-Learning Algorithms. IEEE Trans. Mob. Comput. Paulos Charonyktakis, Maria Plakia, Ioannis Tsamardinos, Maria Papadopouli
2016	Misc	`conf`	SCENERY: A Web-Based Application for Network Reconstruction and Visualization of Cytometry Data. PACBB Giorgos Athineou, Giorgos Papoutsoglou, Sofia Triantafillou, Ioannis Basdekis, Vincenzo Lagani, Ioannis Tsamardinos
2016	—	`conf`	Score-based vs Constraint-based Causal Learning in the Presence of Confounders. CFA@UAI Sofia Triantafillou, Ioannis Tsamardinos
2016	A*	`conf`	Towards Robust and Versatile Causal Discovery for Business Applications. KDD Giorgos Borboudakis, Ioannis Tsamardinos
2015	A	`conf`	Bayesian Network Learning with Discrete Case-Control Data. UAI Giorgos Borboudakis, Ioannis Tsamardinos
2015	J	`jnl`	Constraint-based causal discovery from multiple interventions over overlapping variable sets. J. Mach. Learn. Res. Sofia Triantafillou, Ioannis Tsamardinos
2015	A*	`conf`	Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning. KDD Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos
2015	J	`jnl`	Performance-Estimation Properties of Cross-Validation-Based Protocols with Simultaneous Hyper-Parameter Optimization. Int. J. Artif. Intell. Tools Ioannis Tsamardinos, Amin Rakhshani, Vincenzo Lagani
2015	Misc	`conf`	T-ReCS: Stable Selection of Dynamically Formed Groups of Features with Application to Prediction of Clinical Outcomes. Pacific Symposium on Biocomputing Grace T. Huang, Ioannis Tsamardinos, Vineet K. Raghu, Naftali Kaminski, Panayiotis V. Benos
2014	J	`jnl`	Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets. CoRR Sofia Triantafilou, Ioannis Tsamardinos
2014	J	`jnl`	Discovering and Exploiting Entailment Relationships in Multi-Label Learning. CoRR Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos
2014	J	`jnl`	Don't use a cannon to kill the ... miRNA mosquito. Bioinform. Nestoras Karathanasis, Ioannis Tsamardinos, Panayiota Poirazi
2014	—	`conf`	Learning Neighborhoods of High Confidence in Constraint-Based Causal Discovery. Probabilistic Graphical Models Sofia Triantafilou, Ioannis Tsamardinos, Anna Roumpelaki
2014	—	`conf`	Performance-Estimation Properties of Cross-Validation-Based Protocols with Simultaneous Hyper-Parameter Optimization. SETN Ioannis Tsamardinos, Amin Rakhshani, Vincenzo Lagani
2014	J	`jnl`	Scoring and Searching over Bayesian Networks with Causal and Associative Priors. CoRR Giorgos Borboudakis, Ioannis Tsamardinos
2013	C	`conf`	A bioinformatics approach for investigating the determinants of Drosha processing. BIBE Nestoras Karathanasis, Ioannis Tsamardinos, Panayiota Poirazi
2013	A	`conf`	Scoring and Searching over Bayesian Networks with Causal and Associative Priors. UAI Giorgos Borboudakis, Ioannis Tsamardinos
2012	—	`conf`	A Methodological Framework for Statistical Analysis of Social Text Streams. ISIP Sophia Kleisarchaki, Dimitris Kotzinos, Ioannis Tsamardinos, Vassilis Christophides
2012	A*	`conf`	Incorporating Causal Prior Knowledge as Path-Constraints in Bayesian Networks and Maximal Ancestral Graphs. ICML Giorgos Borboudakis, Ioannis Tsamardinos
2012	—	`conf`	Learning from Mixture of Experimental Data: A Constraint-Based Approach. SETN Vincenzo Lagani, Ioannis Tsamardinos, Sofia Triantafilou
2012	C	`conf`	SVM-based miRNA: MiRNA∗ duplex prediction. BIBE Nestoras Karathanasis, Ioannis Tsamardinos, Angelos P. Armen, Panayiota Poirazi
2012	J	`jnl`	Scoring Bayesian Networks with Informative, Causal and Associative Priors CoRR Giorgos Borboudakis, Ioannis Tsamardinos
2012	J	`jnl`	To feature space and back: Identifying top-weighted features in polynomial Support Vector Machine models. Intell. Data Anal. Laura E. Brown, Ioannis Tsamardinos, Douglas P. Hardin
2012	J	`jnl`	Towards Integrative Causal Analysis of Heterogeneous Data Sets and Studies. J. Mach. Learn. Res. Ioannis Tsamardinos, Sofia Triantafilou, Vincenzo Lagani
2011	B	`conf`	A constraint-based approach to incorporate prior knowledge in causal models. ESANN Giorgos Borboudakis, Sofia Triantafilou, Vincenzo Lagani, Ioannis Tsamardinos
2011	B	`conf`	A unified approach to estimation and control of the False Discovery Rate in Bayesian network skeleton identification. ESANN Angelos P. Armen, Ioannis Tsamardinos
2011	C	`conf`	Information-Preserving Techniques Improve Chemosensitivity Prediction of Tumours Based on Expression Profiles. EANN Eleni G. Christodoulou, O. D. Røe, Amos Folarin, Ioannis Tsamardinos
2011	—	`conf`	Risk Assessment Models for Diabetes Complications: A Survey of Available Online Tools. MobiHealth Lefteris Koumakis, Franco Chiarugi, Vincenzo Lagani, Angelina Kouroubali, Ioannis Tsamardinos
2011	—	`conf`	Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition. AmI Chrysi Filippaki, Grigoris Antoniou, Ioannis Tsamardinos
2010	A	`conf`	Learning Causal Structure from Overlapping Variable Sets. AISTATS Sofia Triantafilou, Ioannis Tsamardinos, Ioannis G. Tollis
2010	J	`jnl`	Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation. J. Mach. Learn. Res. Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
2010	J	`jnl`	Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions. J. Mach. Learn. Res. Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos
2010	—	`conf`	Permutation Testing Improves Bayesian Network Learning. ECML/PKDD (3) Ioannis Tsamardinos, Giorgos Borboudakis
2010	J	`jnl`	Structure-based variable selection for survival data. Bioinform. Vincenzo Lagani, Ioannis Tsamardinos
2009	Misc	`conf`	Multi-Source Causal Analysis: Learning Bayesian Networks from Multiple Datasets. AIAI Ioannis Tsamardinos, Asimakis P. Mariglis
2008	—	`conf`	A Strategy for Making Predictions Under Manipulation. WCCI Causation and Prediction Challenge Laura E. Brown, Ioannis Tsamardinos
2008	A*	`conf`	Bounding the False Discovery Rate in Local Bayesian Network Learning. AAAI Ioannis Tsamardinos, Laura E. Brown
2007	J	`jnl`	Causal Data Mining in Bioinformatics. ERCIM News Ioannis Tsamardinos
2006	Misc	`conf`	Generating Realistic Large Bayesian Networks by Tiling. FLAIRS Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown, Constantin F. Aliferis
2006	J	`jnl`	The max-min hill-climbing Bayesian network structure learning algorithm. Mach. Learn. Ioannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis
2005	Misc	`conf`	A Comparison of Bayesian Network Learning Algorithms from Continuous Data. AMIA Lawrence D. Fu, Ioannis Tsamardinos
2005	A*	`conf`	A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms. AAAI Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
2005	J	`jnl`	A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis. Bioinform. Alexander R. Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos, Douglas P. Hardin, Shawn Levy
2005	J	`jnl`	GEMS: A system for automated cancer diagnosis and biomarker discovery from microarray gene expression data. Int. J. Medical Informatics Alexander R. Statnikov, Ioannis Tsamardinos, Yerbolat Dosbayev, Constantin F. Aliferis
2005	J	`jnl`	Research Paper: Text Categorization Models for High-Quality Article Retrieval in Internal Medicine. J. Am. Medical Informatics Assoc. Yindalon Aphinyanaphongs, Ioannis Tsamardinos, Alexander R. Statnikov, Douglas P. Hardin, Constantin F. Aliferis
2005	Misc	`conf`	Using the AMIA Alexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis
2005	A*	`conf`	Using the GEMS System for Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data. AAAI Alexander R. Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis
2004	—	`conf`	A Novel Algorithm for Scalable and Accurate Bayesian Network Learning. MedInfo Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
2004	A*	`conf`	A theoretical characterization of linear SVM-based feature selection. ICML Douglas P. Hardin, Ioannis Tsamardinos, Constantin F. Aliferis
2004	—	`conf`	Methods for Multi-Category Cancer Diagnosis from Gene Expression Data: A Comprehensive Evaluation to Inform Decision Support System Development. MedInfo Alexander R. Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos
2003	Misc	`conf`	Algorithms for Large Scale Markov Blanket Discovery. FLAIRS Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
2003	J	`jnl`	Autominder: an intelligent cognitive orthotic system for people with memory impairment. Robotics Auton. Syst. Martha E. Pollack, Laura E. Brown, Dirk Colbry, Colleen E. McCarthy, Cheryl Orosz, Bart Peintner, Sailesh Ramakrishnan, Ioannis Tsamardinos
2003	J	`jnl`	CTP: A New Constraint-Based Formalism for Conditional, Temporal Planning. Constraints An Int. J. Ioannis Tsamardinos, Thierry Vidal, Martha E. Pollack
2003	—	`conf`	Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery. METMBS Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown
2003	J	`jnl`	Efficient solution techniques for disjunctive temporal reasoning problems. Artif. Intell. Ioannis Tsamardinos, Martha E. Pollack
2003	Misc	`conf`	HITON: A Novel Markov Blanket Algorithm for Optimal Variable Selection. AMIA Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov
2003	A*	`conf`	Identifying Markov Blankets with Decision Tree Induction. ICDM Lewis J. Frey, Douglas H. Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
2003	Misc	`conf`	Machine Learning Models for Classification of Lung Cancer and Selection of Genomic Markers Using Array Gene Expression Data. FLAIRS Constantin F. Aliferis, Ioannis Tsamardinos, Pierre P. Massion, Alexander R. Statnikov, Nafeh Fananapazir, Douglas P. Hardin
2003	A*	`conf`	Time and sample efficient discovery of Markov blankets and direct causal relations. KDD Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
2003	A	`conf`	Towards Principled Feature Selection: Relevancy, Filters and Wrappers. AISTATS Ioannis Tsamardinos, Constantin F. Aliferis
2003	—	`conf`	Why Classification Models Using Array Gene Expression Data Perform So Well: A Preliminary Investigation of Explanatory Factors. METMBS Constantin F. Aliferis, Ioannis Tsamardinos, Pierre P. Massion, Alexander R. Statnikov, Douglas P. Hardin
2002	—	`conf`	A Probabilistic Approach to Robust Execution of Temporal Plans with Uncertainty. SETN Ioannis Tsamardinos
2002	—	`conf`	A Scheme for Integrating e-Services in Establishing Virtual Enterprises. RIDE Alan Berfield, Panos K. Chrysanthis, Ioannis Tsamardinos, Martha E. Pollack, Sujata Banerjee
2001	—	`conf`	Execution-Time Plan Management for a Cognitive Orthotic System. Advances in Plan-Based Control of Robotic Agents Martha E. Pollack, Colleen E. McCarthy, Sailesh Ramakrishnan, Ioannis Tsamardinos
2000	—	`conf`	Merging Plans with Quantitative Temporal Constraints, Temporally Extended Actions, and Conditional Branches. AIPS Ioannis Tsamardinos, Martha E. Pollack, John F. Horty
1998	—	`conf`	Fast Transformation of Temporal Plans for Efficient Execution. AAAI/IAAI Ioannis Tsamardinos, Nicola Muscettola, Paul H. Morris
1998	A*	`conf`	Reformulating Temporal Plans for Efficient Execution. KR Nicola Muscettola, Paul H. Morris, Ioannis Tsamardinos
1998	J	`jnl`	The potential for the evolution of co-operation among web agents. Int. J. Hum. Comput. Stud. Cristina Bicchieri, Martha E. Pollack, Carlo Rovelli, Ioannis Tsamardinos