School of Informatics AUTh
I. Partalas, G. Tsoumakas, I. Vlahavas (2010) “An Ensemble Uncertainty Aware Measure for Directed Hill Climbing Ensemble Pruning”, Machine Learning 81(3), pp. 257-282.
I. Katakis, G. Tsoumakas, I. Vlahavas, “Tracking Recurring Contexts using Ensemble Classifiers: An Application to Email Filtering”, Knowledge and Information Systems, Springer, 22(3), pp. 371-391, 2010.
I. Partalas, G. Tsoumakas, I. Vlahavas (2009) “Pruning an Ensemble of Classifiers via Reinforcement Learning”, Neurocomputing, Elsevier, 72(7-9), pp. 1900-1909.
I. Katakis, G. Tsoumakas, E. Banos, N. Bassiliades, I. Vlahavas, “An Adaptive Personalized News Dissemination System”, Journal of Intelligent Information Systems, Springer, 32 (2), pp. 191-212, 2009.
I. Partalas, G. Tsoumakas, E. Hatzikos, I. Vlahavas (2008) “Greedy Regression Ensemble Selection: Theory and an Application to Water Quality”, Information Sciences, Elsevier, 178(20), pp. 3867-3879.
E. Hatzikos, G. Tsoumakas, G. Tzanis, N. Bassiliades, I. Vlahavas, “An Empirical Study of Sea Water Quality Prediction”, Knowledge-Based Systems, Elsevier, 21(6), pp. 471-478, 2008.
G. Tsoumakas, I. Katakis, “Multi Label Classification: An Overview”, International Journal of Data Warehousing and Mining, David Taniar (Ed.), Idea Group Publishing, 3(3), pp. 1-13, 2007.
G. Tsoumakas, I. Vlahavas, “An interoperable and scalable Web-based system for classifier sharing and fusion”, Expert Systems with Applications, Elsevier, 33(3), pp. 716-724, 2007.
G. Tsoumakas, L. Angelis, I. Vlahavas (2005) “Selective Fusion of Heterogeneous Classifiers”, Intelligent Data Analysis, IOS Press, 9(6), pp. 511-525.
G. Tsoumakas, L. Angelis, I. Vlahavas, “Clustering Classifiers for Knowledge Discovery from Physically Distributed Databases”, Data and Knowledge Engineering, Elsevier, 49(3), pp. 223-242, 2004.
