• Sorted by Date • Classified by Publication Type •

Classified by Publication Type

• Journal • Refereed Conference • Refereed Workshop • Book Chapter •

Journal

• Ioannis Partalas, Grigorios Tsoumakas, and Ioannis Vlahavas. An ensemble uncertainty aware measure for directed hill climbing ensemble pruning. Machine Learning, 81:257–282, 2010.
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• Ioannis Partalas, Grigorios Tsoumakas, and Ioannis Vlahavas. Pruning an Ensemble of Classifiers via Reinforcement Learning. Neurocomputing, 72(7-9):1900–1909, Elsevier, 2008.
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• Ioannis Partalas, Ioannis Feneris, and Ioannis Vlahavas. A Hybrid Multiagent Reinforcement Learning Approach using Strategies and Fusion. International Journal on Artificial Intelligence Tools, 17(5):945–962, 2008.
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• Ioannis Partalas, Grigorios Tsoumakas, Evaggelos Hatzikos, and Ioannis Vlahavas. Greedy Regression Ensemble Selection: Theory and an Application to Water Quality Prediction. Information Sciences, 178:3867–3879, Elsevier, 2008.
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Refereed Conference

• Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, and Ioannis Vlahavas. Transferring Models in Hybrid Reinforcement Learning Agents. In 12th Engineering Applications of Neural Networks, 2011.
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• Ioannis Partalas, Grigorios Tsoumakas, Konstantinos Tzevanidis, and Ioannis Vlahavas. Transferring Experience in Reinforcement Learning through Task Decomposition. In AAMAS 09, International Conference on Autonomous Agents and Multiagent Systems, pp. 1193–1194, 2009.
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• Ioannis Partalas, Grigorios Tsoumakas, and Ioannis Vlahavas. Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection. In 19th European Conference on Artificial Intelligence, pp. 117–121, 2008.
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• Ioannis Partalas, Georgios Paliouras, and Ioannis Vlahavas. Reinforcement Learning with Classifier Selection for Focused Crawling. In 19th European Conference on Artificial Intelligence, pp. 759–760, 2008.
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• Ioannis Partalas, Ioannis Feneris, and Ioannis Vlahavas. Multi-Agent Reinforcement Learning using Strategies and Voting. In 19th IEEE International Conference on Tools with Artificial Intelligence, pp. 318–324, 2007.
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• Ioannis Partalas, Evaggelos Hatzikos, Grigorios Tsoumakas, and Ioannis Vlahavas. Ensemble Selection for Water Quality Prediction. In International Conference on Enginnering Applications of Neural Networks, 2007.
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• I. Partalas, G. Tsoumakas, I. Katakis, and I. Vlahavas. Ensemble Pruning using Reinforcement Learning. In 4th Hellenic Conference on Artificial Intelligence (SETN 2006), pp. 301–310, 2006.
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• Georgios Tzanis, Ioannis Katakis, Ioannis Partalas, and Ioannis Vlahavas. Modern Applications of Machine Learning. In Annual SEERC Doctoral Student Conference, 2006.
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Refereed Workshop

• Georgios Boutsioukis, Ioannis Partalas, and Ioannis Vlahavas. Transfer Learning in Multi-agent Reinforcement Learning Domains. In 9th European Workshop on Reinforcement Learning, 2011.
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• Kyriakos Chatzidimitriou, Ioannis Partalas, Pericles Mitkas, and Ioannis Vlahavas. Transferring Evolved Reservoir Features in Reinforcement Learning Tasks. In 9th European Workshop on Reinforcement Learning, 2011.
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• Anestis Fachantidis, Ioannis Partalas, Matthew Taylor, and Ioannis Vlahavas. Transfer Learning via Multiple Inter-Task Mappings. In 9th European Workshop on Reinforcement Learning, 2011.
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• Grigorios Tsoumakas, Ioannis Partalas, and Ioannis Vlahavas. A Taxonomy and Short Review of Ensemble Selection. In ECAI 08, Workshop on Supervised and Unsupervised Ensemble Methods and Their Applications, SUEMA, 2008.
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Book Chapter

• Grigorios Tsoumakas, Ioannis Partalas, and Ioannis Vlahavas. An Ensemble Pruning Primer. In Oleg Okun and Giorgio Valentini, editors, Applications of supervised and unsupervised ensemble methods, pp. 1–13, Springer Verlag, 2009.
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• Ioannis Partalas, Dimitrios Vrakas, and Ioannis Vlahavas. Reinforcement Learning and Automated Planning: A Survey. In Dimitrios Vrakas and Ioannis Vlahavas, editors, Advanced Problem Solving Techniques, IGI Global, 2008.
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