Ioannis Partalas

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Eric GaussierProfessor Univ. Grenoble AlpesVerified email at imag.fr
Ioannis VlahavasProfessor of Computer Science, Aristotle University of Thessaloniki, GreeceVerified email at csd.auth.gr
Georgios BalikasSalesforce, GrenobleVerified email at salesforce.com
Grigorios TsoumakasAristotle University of ThessalonikiVerified email at csd.auth.gr
Georgios PaliourasNational Center for Scientific Research "Demokritos", Athens, GreeceVerified email at iit.demokritos.gr
Patrick GallinariProfessor Sorbonne University / Criteo AI LabVerified email at sorbonne-universite.fr
Thierry ArtieresProfesseur d'informatique, Ecole Centrale Marseille, LIS, Aix-Marseille Université, CNRSVerified email at lis-lab.fr
Massih-Reza AminiProfessor, University Grenoble AlpesVerified email at imag.fr
Nicolas BaskiotisLIP6, UPMCVerified email at lip6.fr
Ion AndroutsopoulosProfessor, Department of Informatics, Athens University of Economics and BusinessVerified email at aueb.gr
Anastasia KritharaPost-doctoral Researcher in National Center for Scientific Research "Demokritos", Athens, GreeceVerified email at iit.demokritos.gr
Rohit BabbarUniversity of Bath, UK and Aalto University, Helsinki, FinlandVerified email at aalto.fi
Axel-Cyrille Ngonga NgomoProfessor of Data Science at Paderborn UniversityVerified email at upb.de
Aris KosmopoulosNCSR Demokritos & SciFY PNPCVerified email at iit.demokritos.gr
Prodromos MalakasiotisPrincipal Machine Learning Engineer at WorkableVerified email at aueb.gr
Petridis SergiosElsevierVerified email at elsevier.com
Anestis FachantidisResearcher - Co-founder, Medoid AIVerified email at csd.auth.gr
Cédric LopezEmvista, research directorVerified email at emvista.com
Dimitris PolychronopoulosDirector, In Silico Biology @Ochre BioVerified email at ochre-bio.com
Michael SchroederProfessor in Bioinformatics, TU DresdenVerified email at biotec.tu-dresden.de

Ioannis Partalas

Machine Learning Scientist

Verified email at expediagroup.com - Homepage

Machine Learning


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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), 1-28, 2015	648	2015
Lshtc: A benchmark for large-scale text classification I Partalas, A Kosmopoulos, N Baskiotis, T Artieres, G Paliouras, ... arXiv preprint arXiv:1503.08581, 2015	189	2015
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	165	2013
An ensemble pruning primer G Tsoumakas, I Partalas, I Vlahavas Applications of supervised and unsupervised ensemble methods, 1-13, 2009	161	2009
An ensemble uncertainty aware measure for directed hill climbing ensemble pruning I Partalas, G Tsoumakas, I Vlahavas Machine Learning 81, 257-282, 2010	127	2010
Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection. I Partalas, G Tsoumakas, IP Vlahavas ECAI, 117-121, 2008	111	2008
Pruning an ensemble of classifiers via reinforcement learning I Partalas, G Tsoumakas, I Vlahavas Neurocomputing 72 (7-9), 1900-1909, 2009	110	2009
A taxonomy and short review of ensemble selection G Tsoumakas, I Partalas, I Vlahavas Workshop on Supervised and Unsupervised Ensemble Methods and Their …, 2008	102	2008
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	87	2013
Transfer Learning in Multi-agent Reinforcement Learning Domains G Boutsioukis, I Partalas, I Vlahavas	72	2012
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	69	2008
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	63	2006
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	37	2006
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	35	2014
A study on greedy algorithms for ensemble pruning I Partalas, G Tsoumakas, I Vlahavas Aristotle University of Thessaloniki, Thessaloniki, Greece, 2012	35	2012
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	34	2015
Transferring task models in reinforcement learning agents A Fachantidis, I Partalas, G Tsoumakas, I Vlahavas Neurocomputing 107, 23-32, 2013	34	2013
Learning taxonomy adaptation in large-scale classification R Babbar, I Partalas, E Gaussier, MR Amini, C Amblard The Journal of Machine Learning Research 17 (1), 3350-3386, 2016	33	2016
On power law distributions in large-scale taxonomies R Babbar, C Metzig, I Partalas, E Gaussier, MR Amini ACM SIGKDD explorations newsletter 16 (1), 47-56, 2014	27	2014
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	26	2015

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