2009 |
21 | EE | Ioannis Partalas,
Grigorios Tsoumakas,
Ioannis P. Vlahavas:
Pruning an ensemble of classifiers via reinforcement learning.
Neurocomputing 72(7-9): 1900-1909 (2009) |
2008 |
20 | EE | Ioannis Partalas,
Grigorios Tsoumakas,
Ioannis P. Vlahavas:
Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection.
ECAI 2008: 117-121 |
19 | EE | Ioannis Katakis,
Grigorios Tsoumakas,
Ioannis P. Vlahavas:
An Ensemble of Classifiers for coping with Recurring Contexts in Data Streams.
ECAI 2008: 763-764 |
18 | EE | E. Spyromitros,
Grigorios Tsoumakas,
Ioannis P. Vlahavas:
An Empirical Study of Lazy Multilabel Classification Algorithms.
SETN 2008: 401-406 |
17 | EE | Stamatia Bibi,
Grigorios Tsoumakas,
Ioannis Stamelos,
Ioannis P. Vlahavas:
Regression via Classification applied on software defect estimation.
Expert Syst. Appl. 34(3): 2091-2101 (2008) |
16 | EE | Ioannis Partalas,
Grigorios Tsoumakas,
Evaggelos V. Hatzikos,
Ioannis P. Vlahavas:
Greedy regression ensemble selection: Theory and an application to water quality prediction.
Inf. Sci. 178(20): 3867-3879 (2008) |
15 | EE | Evaggelos V. Hatzikos,
Grigorios Tsoumakas,
George Tzanis,
Nick Bassiliades,
Ioannis P. Vlahavas:
An empirical study on sea water quality prediction.
Knowl.-Based Syst. 21(6): 471-478 (2008) |
2007 |
14 | EE | Grigorios Tsoumakas,
Ioannis P. Vlahavas:
Random k -Labelsets: An Ensemble Method for Multilabel Classification.
ECML 2007: 406-417 |
13 | EE | Grigorios Tsoumakas,
Ioannis P. Vlahavas:
An interoperable and scalable Web-based system for classifier sharing and fusion.
Expert Syst. Appl. 33(3): 716-724 (2007) |
2006 |
12 | EE | E. Banos,
Ioannis Katakis,
Nick Bassiliades,
Grigorios Tsoumakas,
Ioannis P. Vlahavas:
PersoNews: A Personalized News Reader Enhanced by Machine Learning and Semantic Filtering.
OTM Conferences (1) 2006: 975-982 |
11 | EE | Ioannis Partalas,
Grigorios Tsoumakas,
Ioannis Katakis,
Ioannis P. Vlahavas:
Ensemble Pruning Using Reinforcement Learning.
SETN 2006: 301-310 |
2005 |
10 | EE | Ioannis Katakis,
Grigorios Tsoumakas,
Ioannis P. Vlahavas:
On the Utility of Incremental Feature Selection for the Classification of Textual Data Streams.
Panhellenic Conference on Informatics 2005: 338-348 |
9 | EE | Sotiris Diplaris,
Grigorios Tsoumakas,
Pericles A. Mitkas,
Ioannis P. Vlahavas:
Protein Classification with Multiple Algorithms.
Panhellenic Conference on Informatics 2005: 448-456 |
8 | EE | Dimitris Vrakas,
Grigorios Tsoumakas,
Nick Bassiliades,
Ioannis P. Vlahavas:
HAPRC: an automatically configurable planning system.
AI Commun. 18(1): 41-60 (2005) |
7 | EE | Grigorios Tsoumakas,
Lefteris Angelis,
Ioannis P. Vlahavas:
Selective fusion of heterogeneous classifiers.
Intell. Data Anal. 9(6): 511-525 (2005) |
2004 |
6 | | Grigorios Tsoumakas,
Dimitris Vrakas,
Nick Bassiliades,
Ioannis P. Vlahavas:
Lazy Adaptive Multicriteria Planning.
ECAI 2004: 693-697 |
5 | EE | Grigorios Tsoumakas,
Ioannis Katakis,
Ioannis P. Vlahavas:
Effective Voting of Heterogeneous Classifiers.
ECML 2004: 465-476 |
4 | EE | Grigorios Tsoumakas,
Dimitris Vrakas,
Nick Bassiliades,
Ioannis P. Vlahavas:
Using the k-Nearest Problems for Adaptive Multicriteria Planning.
SETN 2004: 132-141 |
3 | EE | Grigorios Tsoumakas,
Lefteris Angelis,
Ioannis P. Vlahavas:
Clustering classifiers for knowledge discovery from physically distributed databases.
Data Knowl. Eng. 49(3): 223-242 (2004) |
2003 |
2 | | Dimitris Vrakas,
Grigorios Tsoumakas,
Nick Bassiliades,
Ioannis P. Vlahavas:
Learning Rules for Adaptive Planning.
ICAPS 2003: 82-91 |
2002 |
1 | | Grigorios Tsoumakas,
Ioannis P. Vlahavas:
Effective Stacking of Distributed Classifiers.
ECAI 2002: 340-344 |