Ioannis Partalas

Publication Activity (10 Years)

Years Active: 2006-2021
Publications (10 Years): 17

Top Topics

Hierarchical Classification

Transfer Learning

Semantic Indexing

Top Venues

Publications

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)
Ioannis Partalas
Aligning Hotel Embeddings using Domain Adaptation for Next-Item Recommendation. CoRR (2021)
Tiago Cunha, Ioannis Partalas, Phong Nguyen
Juggler: Multi-Stakeholder Ranking with Meta-Learning. MORS@RecSys (2021)
Ali Sadeghian, Shervin Minaee, Ioannis Partalas, Xinxin Li, Daisy Zhe Wang, Brooke Cowan
Hotel2vec: Learning Attribute-Aware Hotel Embeddings with Self-Supervision. CoRR (2019)
Georgios Balikas, Ioannis Partalas
Wasserstein distances for evaluating cross-lingual embeddings. CoRR (2019)
Georgios Balikas, Ioannis Partalas
On the Effectiveness of Feature Set Augmentation Using Clusters of Word Embeddings. SwissText (2018)
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 (2017)
Georgios Balikas, Ioannis Partalas, Massih-Reza Amini
On the effectiveness of feature set augmentation using clusters of word embeddings. CoRR (2017)
Namrata Patel, Cédric Lopez, Ioannis Partalas, Frédérique Segond
Une approche hybride pour la détection d'influenceurs dans les médias sociaux. IC (2017)
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)
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)
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)
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 (2017)
Ioannis Partalas, Cédric Lopez, Frédérique Segond
Comparing Named-Entity Recognizers in a Targeted Domain: Handcrafted Rules vs Machine Learning. JEP-TALN-RECITAL (Posters) (2016)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini, Cécile Amblard
Learning Taxonomy Adaptation in Large-scale Classification. J. Mach. Learn. Res. 17 (2016)
Ioannis Partalas, Georgios Balikas
e-Commerce product classification: our participation at cDiscount 2015 challenge. CoRR (2016)
Ioannis Partalas, Cédric Lopez, Nadia Derbas, Ruslan Kalitvianski
Learning to Search for Recognizing Named Entities in Twitter. NUT@COLING (2016)
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 (2015)
Georgios Balikas, Ioannis Partalas, Éric Gaussier, Rohit Babbar, Massih-Reza Amini
Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data. IDA (2015)
Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Liva Ralaivola, Nicolas Usunier, Éric Gaussier
On Binary Reduction of Large-Scale Multiclass Classification Problems. IDA (2015)
Vasiliki Sfyrla, Ioannis Partalas, Richard Yann, Sebastian Maunoury
Learning semantic models from event logs. BPM (Industry Track) (2015)
Daniel Hernández-Lobato, Ioannis Katakis, Gonzalo Martínez-Muñoz, Ioannis Partalas
Special Issue on "Solving complex machine learning problems with ensemble methods". Neurocomputing 150 (2015)
Georgios Balikas, Anastasia Krithara, Ioannis Partalas, George Paliouras
BioASQ: A Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering. MRDM@ECIR (2015)
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 (2015)
Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas
Transfer learning with probabilistic mapping selection. Adapt. Behav. 23 (1) (2015)
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) (2015)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
Re-ranking approach to classification in large-scale power-law distributed category systems. SIGIR (2014)
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)
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)
Rohit Babbar, Cornelia Metzig, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
On power law distributions in large-scale taxonomies. SIGKDD Explor. 16 (1) (2014)
Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas
An Autonomous Transfer Learning Algorithm for TD-Learners. SETN (2014)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
On Flat versus Hierarchical Classification in Large-Scale Taxonomies. NIPS (2013)
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)
Aris Kosmopoulos, Ioannis Partalas, Éric Gaussier, Georgios Paliouras, Ion Androutsopoulos
Evaluation Measures for Hierarchical Classification: a unified view and novel approaches. CoRR (2013)
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)
Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
Transferring task models in Reinforcement Learning agents. Neurocomputing 107 (2013)
Ioannis Partalas, Éric Gaussier, Axel-Cyrille Ngonga Ngomo
Results of the First BioASQ Workshop. BioASQ@CLEF (2013)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
Maximum-Margin Framework for Training Data Synchronization in Large-Scale Hierarchical Classification. ICONIP (1) (2013)
Ioannis Partalas, Rohit Babbar, Éric Gaussier, Cécile Amblard
Adaptive Classifier Selection in Large-Scale Hierarchical Classification. ICONIP (3) (2012)
Rohit Babbar, Ioannis Partalas, Éric Gaussier, Cécile Amblard
On empirical tradeoffs in large scale hierarchical classification. CIKM (2012)
Kyriakos C. Chatzidimitriou, Ioannis Partalas, Pericles A. Mitkas, Ioannis P. Vlahavas
Transferring Evolved Reservoir Features in Reinforcement Learning Tasks. EWRL (2011)
Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
Transferring Models in Hybrid Reinforcement Learning Agents. EANN/AIAI (1) (2011)
Georgios Boutsioukis, Ioannis Partalas, Ioannis P. Vlahavas
Transfer Learning in Multi-Agent Reinforcement Learning Domains. EWRL (2011)
Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas
Transfer Learning via Multiple Inter-task Mappings. EWRL (2011)
Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
An ensemble uncertainty aware measure for directed hill climbing ensemble pruning. Mach. Learn. 81 (3) (2010)
Ioannis Partalas, Grigorios Tsoumakas, Konstantinos Tzevanidis, Ioannis P. Vlahavas
Transferring experience in reinforcement learning through task decomposition. AAMAS (2) (2009)
Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
Pruning an ensemble of classifiers via reinforcement learning. Neurocomputing 72 (7-9) (2009)
Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlahavas
A Hybrid Multiagent Reinforcement Learning Approach Using Strategies and Fusion. Int. J. Artif. Intell. Tools 17 (5) (2008)
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) (2008)
Ioannis Partalas, Georgios Paliouras, Ioannis P. Vlahavas
Reinforcement Learning with Classifier Selection for Focused Crawling. ECAI (2008)
Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection. ECAI (2008)
Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlahavas
Multi-agent Reinforcement Learning Using Strategies and Voting. ICTAI (2) (2007)
Ioannis Partalas, Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas
Ensemble Pruning Using Reinforcement Learning. SETN (2006)