RESEARCH
PUBLICATIONS
2009
The Possibility of Integrative Causal Analysis: Learning from Different Datasets and Studies
Ioannis Tsamardinos, Sofia Triantafillou
Journal of Engineering Intelligent Systems 17(1), 2009
Causal Explorer: A Matlab Library of Algorithms for Causal Discovery and Variable Selection for Classification
Statnikov A, Tsamardinos I, Brown LE, Aliferis CF.
Challenges in Causality. Volume 1: Causation and Prediction Challenge. Edited by Guyon I, Aliferis CF, Cooper GF, Elisseeff A, Pellet JP, Spirtes P and Statnikov A. (In press) Brookline, Massachusetts: Microtome Publishing, 2009.
Multi-Source Causal Analysis: Learning Bayesian Networks from Multiple Datasets
Ioannis Tsamardinos and Asimakis P. Mariglis
5th IFIP Conference on Artificial Intelligence Applications & Innovations (AIAI 2009), 2009
Predicting the occurrence of acute hypotensive episodes: The PhysioNet challenge
Chiarugi, F., Karatzanis, I., Sakkalis, V., Tsamardinos, I., Dermitzaki, T., Foukarakis, M., et al. (2009)
Proceedings of Computers in Cardiology 2009 (CinC 2009), Park City, Utah
Factors Influencing the Statistical Power of Complex Data Analysis Protocols for Molecular Signature Development from Microarray Data
Constantin Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Jonathan Schildcrout, Bryan Shepherd, Frank Harrell
PLoS ONE, 2009; 4(3): e4922
2008
A Strategy for Making Predictions Under Manipulation
Laura E. Brown, Ioannis Tsamardinos
Journal of Machine Learning Research (Workshop and Conference Proceedings) 3:35-52, 2008
Bounding the False Discovery Rate in Local Bayesian Network Learning
Ioannis Tsamardinos, Laura E. Brown
Twenty Third AAAI Conference on Artificial Intelligence, 2008 (AAAI-2008)
Morphological classification of heartbeats using similarity features and a two-phase decision tree
Chiarugi, F., Emmanouilidou, D., Tsamardinos, I., & Tollis, I. G. (2008)
Computers in Cardiology 2008, CAR, Bologna. , 35 849-852.
2006
Challenges in the Analysis of Mass-Throughput Data: A Technical Commentary from the Perspective of Statistical Machine Learning
Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos
Cancer Informatics. 2006; 2: 133–162
Generating Realistic Large Bayesian Networks by Tiling
Ioannis Tsamardinos, Alexander Statnikov, Laura E. Brown, Constantin F. Aliferis
19th International FLAIRS conference (FLAIRS), 2006
The Max-Min Hill-Climbing Bayesian Network Structure Learning Algorithm
I. Tsamardinos, L.E. Brown, C.F. Aliferis
Machine Learning Journal; 65: 31-78
2005
A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms
Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI), pp. 739-745, 2005
GEMS: A System for Automated Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data
Alexander Statnikov, Ioannis Tsamardinos, Yerbolat Dosbayev, Constantin F. Aliferis
International Journal of Medical Informatics, 74(7-8):491-503, 2005
Text Categorization Models for High Quality Article Retrieval in Internal Medicine
Yindalon Aphinyanaphongs, Ioannis Tsamardinos, Alexander Statnikov, Douglas Hardin, Constantin F. Aliferis
Journal of American Medical Informatics Association 12(2):207-216, 2005
A Comprehensive Evaluation of Multicategory Classification Methods for Microarray Gene Expression Cancer Diagnosis
Alexander Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos, Douglas Hardin, Shawn Levy
Bioinformatics 21(5):631-643, 2005
2004
A Theoretical Characterization of Linear SVM-Based Feature Selection
Douglas Hardin, Ioannis Tsamardinos, Constantin F. Aliferis
The Twenty-First International Conference on Machine Learning (ICML 2004), 2004
Efficiently Dispatching Plans Encoded as Simple Temporal Problems
Martha E. Pollack, Ioannis Tsamardinos
Intelligent Techniques for Planning, Idea Group Publishing, Editors: Ioannis Vlahavas and Dimitris Vrakas, 2004
A Novel Algorithm for Scalable and Accurate Bayesian Network Learning
Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis
Proceedings of 11th World Congress in Medical Informatics (MEDINFO ’04), 2004
Methods for Multi-Category Cancer Diagnosis from Gene Expression Data: A Comprehensive Evaluation to Inform Decision Support System Development
Alexander Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos
Proceedings of 11th World Congress in Medical Informatics (MEDINFO ’04), 2004, Gold Medal in the Student Paper Competition
2003
Identifying Markov Blankets with Decision Tree Induction
Lewis Frey, Douglas Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander Statnikov
The Third IEEE International Conference on Data Mining (ICDM’03), pp. 59-66.
HITON, A Novel Markov Blanket Algorithm for Optimal Variable Selection
C. F. Aliferis, I. Tsamardinos, A. Statnikov
American Medical Informatics Association meeting 2003 (AMIA 2003)
Time and Sample Efficient Discovery of Markov Blankets and Direct Causal Relations
I. Tsamardinos, C.F. Aliferis, A. Statnikov
The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2003), p. 673-678
Assessing the Probability of Legal Execution of Plans with Temporal Uncertainty
I. Tsamardinos, M. E. Pollack, S. Ramakrishnan
ICAPS03 Workshop on Planning under Uncertainty and Incomplete Information, 2003, p. 110-118.
Autominder: An Intelligent Cognitive Orthotic System for People with Memory Impairment
M. E. Pollack, L. Brown, D. Colbry, C. E. McCarthy, C. Orosz, B. Peintner, S. Ramakrishnan, and I. Tsamardinos
Robotics and Autonomous Systems, 44(3-4):273-282, 2003
Efficient Solution Techniques for Disjunctive Temporal Reasoning Problems
Ioannis Tsamardinos and Martha E. Pollack
Artificial Intelligence, 151(1-2), pp 43-89, 2003
CTP: A New Constraint-Based Formalism for Conditional, Temporal Planning
Ioannis Tsamardinos, Thierry Vidal, Martha E. Pollack
Special Issue on Planning of Constraints Journal, 8:4 October 2003, p. 365-388
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery
Constantin F. Aliferis, Ioannis Tsamardinos, Alexander Statnikov, Laura E. Brown
International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS '03), p. 371-376
Why Classification Models Using Array Gene Expression Data Perform So Well: A Preliminary Investigation Of Explanatory Factors
C. F. Aliferis, I. Tsamardinos, P. Massion, A. Statnikov, D. Hardin
International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS '03), 47-53
Algorithms for Large Scale Markov Blanket Discovery
Ioannis Tsamardinos, Constantin F. Aliferis, Alexander Statnikov
The 16th International FLAIRS Conference, St. Augustine, Florida, USA, May 2003, p. 376-381
Machine Learning Models For Classification Of Lung Cancer and Selection of Genomic Markers Using Array Gene Expression Data
Constantin F. Aliferis, Ioannis Tsamardinos, Pierre Mansion, Alexander Statnikov, Douglas Hardin
The 16th International FLAIRS Conference, St. Augustine, Florida, USA, May 2003, p. 67-71
Towards Principled Feature Selection: Relevancy, Filters, and Wrappers
Ioannis Tsamardinos, Constantin F. Aliferis
Ninth International Workshop on Artificial Intelligence and Statistics, Key West, Florida, USA, January, 2003 (AI&Stats 2003)