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2020 – today
- 2021
[c33]Tiago Cunha, Ioannis Partalas, Phong Nguyen:
Juggler: Multi-Stakeholder Ranking with Meta-Learning. MORS@RecSys 2021- [c32]Ioannis Partalas, Anne Morvan, Ali Sadeghian, Shervin Minaee, Xinxin Li, Brooke Cowan, Daisy Zhe Wang:
Hotel2vec: Learning Hotel Embeddings from User Click Sessions with Side Information. RecTour@RecSys 2021: 69-84 - [i9]Ioannis Partalas:
Aligning Hotel Embeddings using Domain Adaptation for Next-Item Recommendation. CoRR abs/2108.13824 (2021)
2010 – 2019
- 2019
- [i8]Ali Sadeghian, Shervin Minaee, Ioannis Partalas, Xinxin Li, Daisy Zhe Wang, Brooke Cowan:
Hotel2vec: Learning Attribute-Aware Hotel Embeddings with Self-Supervision. CoRR abs/1910.03943 (2019) - [i7]Georgios Balikas, Ioannis Partalas:
Wasserstein distances for evaluating cross-lingual embeddings. CoRR abs/1910.11005 (2019) - 2018
- [c31]Georgios Balikas, Ioannis Partalas:
On the Effectiveness of Feature Set Augmentation Using Clusters of Word Embeddings. SwissText 2018: 26-32 - 2017
- [c30]Ioannis Partalas, Cédric Lopez, Pierre-Alain Avouac, Matthieu Osmuk, Domoina Rabarijaona, Dana Popovici, Frédérique Segond:
A Hybrid Approach for Detecting Influencers in Social Media. EGC 2017: 465-468 - [c29]Namrata Patel, Cédric Lopez, Ioannis Partalas, Frédérique Segond:
Une approche hybride pour la détection d'influenceurs dans les médias sociaux. IC 2017: 115-120 - [c28]Kévin Deturck, Namrata Patel
, Pierre-Alain Avouac, Cédric Lopez, Damien Nouvel, Ioannis Partalas, Frédérique Segond:
Detecting Influencial Users in Social Networks: Analysing Graph-Based and Linguistic Perspectives. AI4KM@IJCAI 2017: 113-131 - [c27]Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov:
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification. NIPS 2017: 4159-4168 - [i6]Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov:
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification. CoRR abs/1701.06511 (2017) - [i5]Georgios Balikas, Ioannis Partalas, Massih-Reza Amini:
On the effectiveness of feature set augmentation using clusters of word embeddings. CoRR abs/1705.01265 (2017) - [i4]Cédric Lopez, Ioannis Partalas, Georgios Balikas, Nadia Derbas, Amélie Martin, Coralie Reutenauer, Frédérique Segond, Massih-Reza Amini:
CAp 2017 challenge: Twitter Named Entity Recognition. CoRR abs/1707.07568 (2017) - 2016
- [j11]Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini, Cécile Amblard:
Learning Taxonomy Adaptation in Large-scale Classification. J. Mach. Learn. Res. 17: 98:1-98:37 (2016) - [c26]Ioannis Partalas, Cédric Lopez, Nadia Derbas, Ruslan Kalitvianski:
Learning to Search for Recognizing Named Entities in Twitter. NUT@COLING 2016: 171-177 - [c25]Ioannis Partalas, Cédric Lopez, Frédérique Segond:
Comparing Named-Entity Recognizers in a Targeted Domain: Handcrafted Rules vs Machine Learning. JEP-TALN-RECITAL (Posters) 2016: 389-395 - [i3]Ioannis Partalas, Georgios Balikas:
e-Commerce product classification: our participation at cDiscount 2015 challenge. CoRR abs/1606.02854 (2016) - 2015
- [j10]Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas:
Transfer learning with probabilistic mapping selection. Adapt. Behav. 23(1): 3-19 (2015) - [j9]George Tsatsaronis, Georgios Balikas, Prodromos Malakasiotis, Ioannis Partalas, Matthias Zschunke, Michael R. Alvers, Dirk Weissenborn, Anastasia Krithara, Sergios Petridis, Dimitris Polychronopoulos, Yannis Almirantis, John Pavlopoulos, Nicolas Baskiotis, Patrick Gallinari, Thierry Artières, Axel-Cyrille Ngonga Ngomo, Norman Heino, Éric Gaussier, Liliana Barrio-Alvers, Michael Schroeder, Ion Androutsopoulos, Georgios Paliouras:
An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition. BMC Bioinform. 16: 138:1-138:28 (2015) - [j8]Aris Kosmopoulos, Ioannis Partalas, Éric Gaussier, Georgios Paliouras, Ion Androutsopoulos:
Evaluation measures for hierarchical classification: a unified view and novel approaches. Data Min. Knowl. Discov. 29(3): 820-865 (2015) - [j7]Daniel Hernández-Lobato, Ioannis Katakis, Gonzalo Martínez-Muñoz, Ioannis Partalas:
Special Issue on "Solving complex machine learning problems with ensemble methods". Neurocomputing 150: 402-403 (2015) - [c24]Vasiliki Sfyrla, Ioannis Partalas, Richard Yann, Sebastian Maunoury:
Learning semantic models from event logs. BPM (Industry Track) 2015: 95-106 - [c23]Georgios Balikas, Anastasia Krithara, Ioannis Partalas, George Paliouras:
BioASQ: A Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering. MRDM@ECIR 2015: 26-39 - [c22]Georgios Balikas, Ioannis Partalas, Éric Gaussier, Rohit Babbar, Massih-Reza Amini:
Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data. IDA 2015: 25-36 - [c21]Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Liva Ralaivola, Nicolas Usunier, Éric Gaussier:
On Binary Reduction of Large-Scale Multiclass Classification Problems. IDA 2015: 132-144 - [i2]Ioannis Partalas, Aris Kosmopoulos, Nicolas Baskiotis, Thierry Artières, George Paliouras, Éric Gaussier, Ion Androutsopoulos, Massih-Reza Amini, Patrick Gallinari:
LSHTC: A Benchmark for Large-Scale Text Classification. CoRR abs/1503.08581 (2015) - 2014
- [j6]Rohit Babbar, Cornelia Metzig, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini:
On power law distributions in large-scale taxonomies. SIGKDD Explor. 16(1): 47-56 (2014) - [c20]Georgios Balikas, Ioannis Partalas, Axel-Cyrille Ngonga Ngomo, Anastasia Krithara, Georgios Paliouras:
Results of the BioASQ Track of the Question Answering Lab at CLEF 2014. CLEF (Working Notes) 2014: 1181-1193 - [c19]Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas:
An Autonomous Transfer Learning Algorithm for TD-Learners. SETN 2014: 57-70 - [c18]Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini:
Re-ranking approach to classification in large-scale power-law distributed category systems. SIGIR 2014: 1059-1062 - [c17]Ioannis Partalas, Massih-Reza Amini, Ion Androutsopoulos, Thierry Artières, Patrick Gallinari, Éric Gaussier, Georgios Paliouras:
Web-scale classification: web classification in the big data era. WSDM 2014: 687-688 - 2013
- [j5]Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Transferring task models in Reinforcement Learning agents. Neurocomputing 107: 23-32 (2013) - [c16]Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas:
Autonomous Selection of Inter-Task Mappings in Transfer Learning (extended abstract). AAAI Spring Symposium: Lifelong Machine Learning 2013 - [c15]Ioannis Partalas, Éric Gaussier, Axel-Cyrille Ngonga Ngomo:
Results of the First BioASQ Workshop. BioASQ@CLEF 2013 - [c14]Rohit Babbar, Ioannis Partalas, Cornelia Metzig, Éric Gaussier, Massih-Reza Amini:
Comparative Classifier Evaluation for Web-Scale Taxonomies Using Power Law. ESWC (Satellite Events) 2013: 310-311 - [c13]Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini:
Maximum-Margin Framework for Training Data Synchronization in Large-Scale Hierarchical Classification. ICONIP (1) 2013: 336-343 - [c12]Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini:
On Flat versus Hierarchical Classification in Large-Scale Taxonomies. NIPS 2013: 1824-1832 - [i1]Aris Kosmopoulos, Ioannis Partalas, Éric Gaussier, Georgios Paliouras, Ion Androutsopoulos:
Evaluation Measures for Hierarchical Classification: a unified view and novel approaches. CoRR abs/1306.6802 (2013) - 2012
- [c11]Rohit Babbar, Ioannis Partalas, Éric Gaussier, Cécile Amblard:
On empirical tradeoffs in large scale hierarchical classification. CIKM 2012: 2299-2302 - [c10]Ioannis Partalas, Rohit Babbar, Éric Gaussier, Cécile Amblard:
Adaptive Classifier Selection in Large-Scale Hierarchical Classification. ICONIP (3) 2012: 612-619 - 2011
- [c9]Kyriakos C. Chatzidimitriou, Ioannis Partalas, Pericles A. Mitkas, Ioannis P. Vlahavas:
Transferring Evolved Reservoir Features in Reinforcement Learning Tasks. EWRL 2011: 213-224 - [c8]Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas:
Transfer Learning via Multiple Inter-task Mappings. EWRL 2011: 225-236 - [c7]Georgios Boutsioukis, Ioannis Partalas, Ioannis P. Vlahavas:
Transfer Learning in Multi-Agent Reinforcement Learning Domains. EWRL 2011: 249-260 - [c6]Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Transferring Models in Hybrid Reinforcement Learning Agents. EANN/AIAI (1) 2011: 162-171 - 2010
- [j4]Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
An ensemble uncertainty aware measure for directed hill climbing ensemble pruning. Mach. Learn. 81(3): 257-282 (2010)
2000 – 2009
- 2009
- [b1]Ioannis Partalas:
Μέθοδοι ενισχυτικής μάθησης σε συστήματα πρακτόρων. Aristotle University Of Thessaloniki, Greece, 2009 - [j3]Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Pruning an ensemble of classifiers via reinforcement learning. Neurocomputing 72(7-9): 1900-1909 (2009) - [c5]Ioannis Partalas, Grigorios Tsoumakas, Konstantinos Tzevanidis, Ioannis P. Vlahavas:
Transferring experience in reinforcement learning through task decomposition. AAMAS (2) 2009: 1193-1194 - [p1]Grigorios Tsoumakas, Ioannis Partalas, Ioannis P. Vlahavas:
An Ensemble Pruning Primer. Applications of Supervised and Unsupervised Ensemble Methods 2009: 1-13 - 2008
- [j2]Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlahavas:
A Hybrid Multiagent Reinforcement Learning Approach Using Strategies and Fusion. Int. J. Artif. Intell. Tools 17(5): 945-962 (2008) - [j1]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) - [c4]Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection. ECAI 2008: 117-121 - [c3]Ioannis Partalas, Georgios Paliouras, Ioannis P. Vlahavas:
Reinforcement Learning with Classifier Selection for Focused Crawling. ECAI 2008: 759-760 - 2007
- [c2]Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlahavas:
Multi-agent Reinforcement Learning Using Strategies and Voting. ICTAI (2) 2007: 318-324 - 2006
- [c1]Ioannis Partalas, Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas:
Ensemble Pruning Using Reinforcement Learning. SETN 2006: 301-310
Coauthor Index
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