Stebėti
Ioannis Partalas
Ioannis Partalas
Machine Learning Scientist, Expedia Group
Patvirtintas el. paštas expediagroup.com - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition
G Tsatsaronis, G Balikas, P Malakasiotis, I Partalas, M Zschunke, ...
BMC bioinformatics 16, 1-28, 2015
6802015
Lshtc: A benchmark for large-scale text classification
I Partalas, A Kosmopoulos, N Baskiotis, T Artieres, G Paliouras, ...
arXiv preprint arXiv:1503.08581, 2015
2132015
Evaluation Measures for Hierarchical Classification: a unified view and novel approaches
A Kosmopoulos, I Partalas, E Gaussier, G Paliouras, I Androutsopoulos
Data Mining and Knowledge Discovery, Springer, 2013
2052013
An ensemble pruning primer
G Tsoumakas, I Partalas, I Vlahavas
Applications of supervised and unsupervised ensemble methods, 1-13, 2009
1772009
An ensemble uncertainty aware measure for directed hill climbing ensemble pruning
I Partalas, G Tsoumakas, I Vlahavas
Machine Learning 81, 257-282, 2010
1352010
Focused ensemble selection: A diversity-based method for greedy ensemble selection
I Partalas, G Tsoumakas, I Vlahavas
ECAI 2008, 117-121, 2008
1152008
A taxonomy and short review of ensemble selection
G Tsoumakas, I Partalas, I Vlahavas
Workshop on Supervised and Unsupervised Ensemble Methods and Their …, 2008
1142008
Pruning an ensemble of classifiers via reinforcement learning
I Partalas, G Tsoumakas, I Vlahavas
Neurocomputing 72 (7-9), 1900-1909, 2009
1122009
On flat versus hierarchical classification in large-scale taxonomies
R Babbar, I Partalas, E Gaussier, MR Amini
Advances in neural information processing systems 26, 2013
962013
Transfer Learning in Multi-agent Reinforcement Learning Domains
G Boutsioukis, I Partalas, I Vlahavas
862012
Greedy regression ensemble selection: Theory and an application to water quality prediction
I Partalas, G Tsoumakas, EV Hatzikos, I Vlahavas
Information Sciences 178 (20), 3867-3879, 2008
842008
Ensemble pruning using reinforcement learning
I Partalas, G Tsoumakas, I Katakis, I Vlahavas
Advances in Artificial Intelligence: 4th Helenic Conference on AI, SETN 2006 …, 2006
642006
Modern applications of machine learning
G Tzanis, I Katakis, I Partalas, I Vlahavas
Proceedings of the 1st Annual SEERC Doctoral Student Conference–DSC 1 (1), 1-10, 2006
532006
BioASQ: a challenge on large-scale biomedical semantic indexing and question answering
G Balikas, A Krithara, I Partalas, G Paliouras
Multimodal Retrieval in the Medical Domain: First International Workshop …, 2015
452015
Learning taxonomy adaptation in large-scale classification
R Babbar, I Partalas, E Gaussier, MR Amini, C Amblard
Journal of Machine Learning Research 17 (98), 1-37, 2016
412016
Results of the BioASQ Track of the Question Answering Lab at CLEF 2014.
G Balikas, I Partalas, ACN Ngomo, A Krithara, G Paliouras
CLEF (Working Notes), 1181-1193, 2014
372014
A study on greedy algorithms for ensemble pruning
I Partalas, G Tsoumakas, I Vlahavas
Aristotle University of Thessaloniki, Thessaloniki, Greece, 2012
352012
Transferring task models in reinforcement learning agents
A Fachantidis, I Partalas, G Tsoumakas, I Vlahavas
Neurocomputing 107, 23-32, 2013
342013
Evaluation framework specifications
G Balikas, I Partalas, A Kosmopoulos, S Petridis, P Malakasiotis, ...
Project deliverable D 4, 2013
322013
Results of the BioASQ tasks of the Question Answering Lab at CLEF 2015
G Balikas, A Kosmopoulos, A Krithara, G Paliouras, I Kakadiaris
CLEF 2015, 2015
292015
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Straipsniai 1–20