Ioannis Partalas

According to our database, Ioannis Partalas authored at least 53 papers between 2006 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Aligning Hotel Embeddings using Domain Adaptation for Next-Item Recommendation.

Ioannis Partalas

CoRR, 2021

Hotel2vec: Learning Hotel Embeddings from User Click Sessions with Side Information.

Ioannis Partalas, Anne Morvan, Ali Sadeghian, Shervin Minaee, Xinxin Li, Brooke Cowan, Daisy Zhe Wang

Proceedings of the Workshop on Recommenders in Tourism co-located with the 15th ACM Conference on Recommender Systems (RecSys 2021), 2021

Juggler: Multi-Stakeholder Ranking with Meta-Learning.

Tiago Cunha, Ioannis Partalas, Phong Nguyen

Proceedings of the 1st Workshop on Multi-Objective Recommender Systems (MORS 2021) co-located with 15th ACM Conference on Recommender Systems (RecSys 2021), 2021

2019

Wasserstein distances for evaluating cross-lingual embeddings.

Georgios Balikas, Ioannis Partalas

CoRR, 2019

Hotel2vec: Learning Attribute-Aware Hotel Embeddings with Self-Supervision.

Ali Sadeghian, Shervin Minaee, Ioannis Partalas, Xinxin Li, Daisy Zhe Wang, Brooke Cowan

CoRR, 2019

2018

On the Effectiveness of Feature Set Augmentation Using Clusters of Word Embeddings.

Georgios Balikas, Ioannis Partalas

Proceedings of the 3rd Swiss Text Analytics Conference, SwissText 2018, Winterthur, 2018

2017

CAp 2017 challenge: Twitter Named Entity Recognition.

Cédric Lopez, Ioannis Partalas, Georgios Balikas, Nadia Derbas, Amélie Martin, Coralie Reutenauer, Frédérique Segond, Massih-Reza Amini

CoRR, 2017

On the effectiveness of feature set augmentation using clusters of word embeddings.

Georgios Balikas, Ioannis Partalas, Massih-Reza Amini

CoRR, 2017

Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification.

Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Detecting Influencial Users in Social Networks: Analysing Graph-Based and Linguistic Perspectives.

Kévin Deturck, Namrata Patel, Pierre-Alain Avouac, Cédric Lopez, Damien Nouvel, Ioannis Partalas, Frédérique Segond

Proceedings of the Artificial Intelligence for Knowledge Management, 2017

Une approche hybride pour la détection d'influenceurs dans les médias sociaux.

Namrata Patel, Cédric Lopez, Ioannis Partalas, Frédérique Segond

Proceedings of the IC 2017 : 28es Journées francophones d'Ingénierie des Connaissances (Proceedings of the 28th French Knowledge Engineering Conference), 2017

A Hybrid Approach for Detecting Influencers in Social Media.

Ioannis Partalas, Cédric Lopez, Pierre-Alain Avouac, Matthieu Osmuk, Domoina Rabarijaona, Dana Popovici, Frédérique Segond

Proceedings of the 17ème Journées Francophones Extraction et Gestion des Connaissances, 2017

2016

Learning Taxonomy Adaptation in Large-scale Classification.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini, Cécile Amblard

J. Mach. Learn. Res., 2016

e-Commerce product classification: our participation at cDiscount 2015 challenge.

Ioannis Partalas, Georgios Balikas

CoRR, 2016

Comparing Named-Entity Recognizers in a Targeted Domain: Handcrafted Rules vs Machine Learning.

Ioannis Partalas, Cédric Lopez, Frédérique Segond

Proceedings of the Actes de la conférence conjointe JEP-TALN-RECITAL 2016. Volume 2 : TALN (Posters), 2016

Learning to Search for Recognizing Named Entities in Twitter.

Ioannis Partalas, Cédric Lopez, Nadia Derbas, Ruslan Kalitvianski

Proceedings of the 2nd Workshop on Noisy User-generated Text, 2016

2015

Special Issue on "Solving complex machine learning problems with ensemble methods".

Daniel Hernández-Lobato, Ioannis Katakis, Gonzalo Martínez-Muñoz, Ioannis Partalas

Neurocomputing, 2015

Evaluation measures for hierarchical classification: a unified view and novel approaches.

Aris Kosmopoulos, Ioannis Partalas, Éric Gaussier, Georgios Paliouras, Ion Androutsopoulos

Data Min. Knowl. Discov., 2015

LSHTC: A Benchmark for Large-Scale Text Classification.

Ioannis Partalas, Aris Kosmopoulos, Nicolas Baskiotis, Thierry Artières, George Paliouras, Éric Gaussier, Ion Androutsopoulos, Massih-Reza Amini, Patrick Gallinari

CoRR, 2015

An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition.

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

BMC Bioinform., 2015

Transfer learning with probabilistic mapping selection.

Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas

Adapt. Behav., 2015

On Binary Reduction of Large-Scale Multiclass Classification Problems.

Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Liva Ralaivola, Nicolas Usunier, Éric Gaussier

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data.

Georgios Balikas, Ioannis Partalas, Éric Gaussier, Rohit Babbar, Massih-Reza Amini

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

BioASQ: A Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering.

Georgios Balikas, Anastasia Krithara, Ioannis Partalas, George Paliouras

Proceedings of the Multimodal Retrieval in the Medical Domain, 2015

Learning semantic models from event logs.

Vasiliki Sfyrla, Ioannis Partalas, Richard Yann, Sebastian Maunoury

Proceedings of the Industry Track at the 13th International Conference on Business Process Management 2015 co-located with 13th International Conference on Business Process Management (BPM 2015), 2015

2014

On power law distributions in large-scale taxonomies.

Rohit Babbar, Cornelia Metzig, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini

SIGKDD Explor., 2014

Web-scale classification: web classification in the big data era.

Ioannis Partalas, Massih-Reza Amini, Ion Androutsopoulos, Thierry Artières, Patrick Gallinari, Éric Gaussier, Georgios Paliouras

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Re-ranking approach to classification in large-scale power-law distributed category systems.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini

Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2014

An Autonomous Transfer Learning Algorithm for TD-Learners.

Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas

Proceedings of the Artificial Intelligence: Methods and Applications, 2014

Results of the BioASQ Track of the Question Answering Lab at CLEF 2014.

Georgios Balikas, Ioannis Partalas, Axel-Cyrille Ngonga Ngomo, Anastasia Krithara, Georgios Paliouras

Proceedings of the Working Notes for CLEF 2014 Conference, 2014

2013

Transferring task models in Reinforcement Learning agents.

Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas

Neurocomputing, 2013

On Flat versus Hierarchical Classification in Large-Scale Taxonomies.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Maximum-Margin Framework for Training Data Synchronization in Large-Scale Hierarchical Classification.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini

Proceedings of the Neural Information Processing - 20th International Conference, 2013

Comparative Classifier Evaluation for Web-Scale Taxonomies Using Power Law.

Rohit Babbar, Ioannis Partalas, Cornelia Metzig, Éric Gaussier, Massih-Reza Amini

Proceedings of the Semantic Web: ESWC 2013 Satellite Events, 2013

Results of the First BioASQ Workshop.

Ioannis Partalas, Éric Gaussier, Axel-Cyrille Ngonga Ngomo

Proceedings of the first Workshop on Bio-Medical Semantic Indexing and Question Answering, 2013

Autonomous Selection of Inter-Task Mappings in Transfer Learning (extended abstract).

Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas

Proceedings of the Lifelong Machine Learning, 2013

2012

Adaptive Classifier Selection in Large-Scale Hierarchical Classification.

Ioannis Partalas, Rohit Babbar, Éric Gaussier, Cécile Amblard

Proceedings of the Neural Information Processing - 19th International Conference, 2012

On empirical tradeoffs in large scale hierarchical classification.

Rohit Babbar, Ioannis Partalas, Éric Gaussier, Cécile Amblard

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011

Transferring Models in Hybrid Reinforcement Learning Agents.

Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Engineering Applications of Neural Networks, 2011

Transfer Learning via Multiple Inter-task Mappings.

Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas

Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

Transferring Evolved Reservoir Features in Reinforcement Learning Tasks.

Kyriakos C. Chatzidimitriou, Ioannis Partalas, Pericles A. Mitkas, Ioannis P. Vlahavas

Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

Transfer Learning in Multi-Agent Reinforcement Learning Domains.

Georgios Boutsioukis, Ioannis Partalas, Ioannis P. Vlahavas

Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

2010

An ensemble uncertainty aware measure for directed hill climbing ensemble pruning.

Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas

Mach. Learn., 2010

2009

An Ensemble Pruning Primer.

Grigorios Tsoumakas, Ioannis Partalas, Ioannis P. Vlahavas

Proceedings of the Applications of Supervised and Unsupervised Ensemble Methods, 2009

Μέθοδοι ενισχυτικής μάθησης σε συστήματα πρακτόρων

Ioannis Partalas

PhD thesis, 2009

Pruning an ensemble of classifiers via reinforcement learning.

Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas

Neurocomputing, 2009

Transferring experience in reinforcement learning through task decomposition.

Ioannis Partalas, Grigorios Tsoumakas, Konstantinos Tzevanidis, Ioannis P. Vlahavas

Proceedings of the 8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), 2009

2008

Greedy regression ensemble selection: Theory and an application to water quality prediction.

Ioannis Partalas, Grigorios Tsoumakas, Evaggelos V. Hatzikos, Ioannis P. Vlahavas

Inf. Sci., 2008

A Hybrid Multiagent Reinforcement Learning Approach Using Strategies and Fusion.

Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlahavas

Int. J. Artif. Intell. Tools, 2008

Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection.

Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the ECAI 2008, 2008

Reinforcement Learning with Classifier Selection for Focused Crawling.

Ioannis Partalas, Georgios Paliouras, Ioannis P. Vlahavas

Proceedings of the ECAI 2008, 2008

2007

Multi-agent Reinforcement Learning Using Strategies and Voting.

Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlahavas

Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), 2007

2006

Ensemble Pruning Using Reinforcement Learning.

Ioannis Partalas, Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas

Proceedings of the Advances in Artificial Intelligence, 4th Helenic Conference on AI, 2006