Ioannis Partalas

56 papers A* 1A 4B 2C 1Journal 20Unranked 26

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Simple Regularization for Aligning Embedding Spaces for Cross-brand Recommendation. RecTour@RecSys Ioannis Partalas
2021	J	`jnl`	Aligning Hotel Embeddings using Domain Adaptation for Next-Item Recommendation. CoRR Ioannis Partalas
2021	—	`conf`	Hotel2vec: Learning Hotel Embeddings from User Click Sessions with Side Information. RecTour@RecSys Ioannis Partalas, Anne Morvan, Ali Sadeghian, Shervin Minaee, Xinxin Li, Brooke Cowan, Daisy Zhe Wang
2021	—	`conf`	Juggler: Multi-Stakeholder Ranking with Meta-Learning. MORS@RecSys Tiago Cunha, Ioannis Partalas, Phong Nguyen
2019	J	`jnl`	Hotel2vec: Learning Attribute-Aware Hotel Embeddings with Self-Supervision. CoRR Ali Sadeghian, Shervin Minaee, Ioannis Partalas, Xinxin Li, Daisy Zhe Wang, Brooke Cowan
2019	J	`jnl`	Wasserstein distances for evaluating cross-lingual embeddings. CoRR Georgios Balikas, Ioannis Partalas
2018	—	`conf`	On the Effectiveness of Feature Set Augmentation Using Clusters of Word Embeddings. SwissText Georgios Balikas, Ioannis Partalas
2017	—	`conf`	A Hybrid Approach for Detecting Influencers in Social Media. EGC Ioannis Partalas, Cédric Lopez, Pierre-Alain Avouac, Matthieu Osmuk, Domoina Rabarijaona, Dana Popovici, Frédérique Segond
2017	—	`conf`	Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification. NIPS Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov
2017	J	`jnl`	Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification. CoRR Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov
2017	J	`jnl`	CAp 2017 challenge: Twitter Named Entity Recognition. CoRR Cédric Lopez, Ioannis Partalas, Georgios Balikas, Nadia Derbas, Amélie Martin, Coralie Reutenauer, Frédérique Segond, Massih-Reza Amini
2017	—	`conf`	Detecting Influencial Users in Social Networks: Analysing Graph-Based and Linguistic Perspectives. AI4KM@IJCAI Kévin Deturck, Namrata Patel, Pierre-Alain Avouac, Cédric Lopez, Damien Nouvel, Ioannis Partalas, Frédérique Segond
2017	J	`jnl`	On the effectiveness of feature set augmentation using clusters of word embeddings. CoRR Georgios Balikas, Ioannis Partalas, Massih-Reza Amini
2017	—	`conf`	Une approche hybride pour la détection d'influenceurs dans les médias sociaux. IC Namrata Patel, Cédric Lopez, Ioannis Partalas, Frédérique Segond
2016	—	`conf`	Comparing Named-Entity Recognizers in a Targeted Domain: Handcrafted Rules vs Machine Learning. JEP-TALN-RECITAL (Posters) Ioannis Partalas, Cédric Lopez, Frédérique Segond
2016	J	`jnl`	Learning Taxonomy Adaptation in Large-scale Classification. J. Mach. Learn. Res. Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini, Cécile Amblard
2016	—	`conf`	Learning to Search for Recognizing Named Entities in Twitter. NUT@COLING Ioannis Partalas, Cédric Lopez, Nadia Derbas, Ruslan Kalitvianski
2016	J	`jnl`	e-Commerce product classification: our participation at cDiscount 2015 challenge. CoRR Ioannis Partalas, Georgios Balikas
2015	J	`jnl`	An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition. BMC Bioinform. 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
2015	—	`conf`	BioASQ: A Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering. MRDM@ECIR Georgios Balikas, Anastasia Krithara, Ioannis Partalas, George Paliouras
2015	B	`conf`	Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data. IDA Georgios Balikas, Ioannis Partalas, Éric Gaussier, Rohit Babbar, Massih-Reza Amini
2015	J	`jnl`	Evaluation measures for hierarchical classification: a unified view and novel approaches. Data Min. Knowl. Discov. Aris Kosmopoulos, Ioannis Partalas, Éric Gaussier, Georgios Paliouras, Ion Androutsopoulos
2015	J	`jnl`	LSHTC: A Benchmark for Large-Scale Text Classification. CoRR Ioannis Partalas, Aris Kosmopoulos, Nicolas Baskiotis, Thierry Artières, George Paliouras, Éric Gaussier, Ion Androutsopoulos, Massih-Reza Amini, Patrick Gallinari
2015	—	`conf`	Learning semantic models from event logs. BPM (Industry Track) Vasiliki Sfyrla, Ioannis Partalas, Richard Yann, Sebastian Maunoury
2015	B	`conf`	On Binary Reduction of Large-Scale Multiclass Classification Problems. IDA Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Liva Ralaivola, Nicolas Usunier, Éric Gaussier
2015	J	`jnl`	Special Issue on "Solving complex machine learning problems with ensemble methods". Neurocomputing Daniel Hernández-Lobato, Ioannis Katakis, Gonzalo Martínez-Muñoz, Ioannis Partalas
2015	J	`jnl`	Transfer learning with probabilistic mapping selection. Adapt. Behav. Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas
2014	—	`conf`	An Autonomous Transfer Learning Algorithm for TD-Learners. SETN Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas
2014	J	`jnl`	On power law distributions in large-scale taxonomies. SIGKDD Explor. Rohit Babbar, Cornelia Metzig, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
2014	A*	`conf`	Re-ranking approach to classification in large-scale power-law distributed category systems. SIGIR Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
2014	—	`conf`	Results of the BioASQ Track of the Question Answering Lab at CLEF 2014. CLEF (Working Notes) Georgios Balikas, Ioannis Partalas, Axel-Cyrille Ngonga Ngomo, Anastasia Krithara, Georgios Paliouras
2014	A	`conf`	Web-scale classification: web classification in the big data era. WSDM Ioannis Partalas, Massih-Reza Amini, Ion Androutsopoulos, Thierry Artières, Patrick Gallinari, Éric Gaussier, Georgios Paliouras
2013	—	`conf`	Autonomous Selection of Inter-Task Mappings in Transfer Learning (extended abstract). AAAI Spring Symposium: Lifelong Machine Learning Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas
2013	—	`conf`	Comparative Classifier Evaluation for Web-Scale Taxonomies Using Power Law. ESWC (Satellite Events) Rohit Babbar, Ioannis Partalas, Cornelia Metzig, Éric Gaussier, Massih-Reza Amini
2013	J	`jnl`	Evaluation Measures for Hierarchical Classification: a unified view and novel approaches. CoRR Aris Kosmopoulos, Ioannis Partalas, Éric Gaussier, Georgios Paliouras, Ion Androutsopoulos
2013	—	`conf`	Maximum-Margin Framework for Training Data Synchronization in Large-Scale Hierarchical Classification. ICONIP (1) Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
2013	—	`conf`	On Flat versus Hierarchical Classification in Large-Scale Taxonomies. NIPS Rohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini
2013	—	`conf`	Results of the First BioASQ Workshop. BioASQ@CLEF Ioannis Partalas, Éric Gaussier, Axel-Cyrille Ngonga Ngomo
2013	J	`jnl`	Transferring task models in Reinforcement Learning agents. Neurocomputing Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
2012	—	`conf`	Adaptive Classifier Selection in Large-Scale Hierarchical Classification. ICONIP (3) Ioannis Partalas, Rohit Babbar, Éric Gaussier, Cécile Amblard
2012	A	`conf`	On empirical tradeoffs in large scale hierarchical classification. CIKM Rohit Babbar, Ioannis Partalas, Éric Gaussier, Cécile Amblard
2011	—	`conf`	Transfer Learning in Multi-Agent Reinforcement Learning Domains. EWRL Georgios Boutsioukis, Ioannis Partalas, Ioannis P. Vlahavas
2011	—	`conf`	Transfer Learning via Multiple Inter-task Mappings. EWRL Anestis Fachantidis, Ioannis Partalas, Matthew E. Taylor, Ioannis P. Vlahavas
2011	—	`conf`	Transferring Evolved Reservoir Features in Reinforcement Learning Tasks. EWRL Kyriakos C. Chatzidimitriou, Ioannis Partalas, Pericles A. Mitkas, Ioannis P. Vlahavas
2011	C	`conf`	Transferring Models in Hybrid Reinforcement Learning Agents. EANN Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
2010	J	`jnl`	An ensemble uncertainty aware measure for directed hill climbing ensemble pruning. Mach. Learn. Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
2009	—	`ch.`	An Ensemble Pruning Primer. Applications of Supervised and Unsupervised Ensemble Methods Grigorios Tsoumakas, Ioannis Partalas, Ioannis P. Vlahavas
2009	J	`jnl`	Pruning an ensemble of classifiers via reinforcement learning. Neurocomputing Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
2009	—	`conf`	Transferring experience in reinforcement learning through task decomposition. AAMAS (2) Ioannis Partalas, Grigorios Tsoumakas, Konstantinos Tzevanidis, Ioannis P. Vlahavas
2009	—	`—`	Μέθοδοι ενισχυτικής μάθησης σε συστήματα πρακτόρων Ioannis Partalas
2008	J	`jnl`	A Hybrid Multiagent Reinforcement Learning Approach Using Strategies and Fusion. Int. J. Artif. Intell. Tools Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlahavas
2008	A	`conf`	Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection. ECAI Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas
2008	J	`jnl`	Greedy regression ensemble selection: Theory and an application to water quality prediction. Inf. Sci. Ioannis Partalas, Grigorios Tsoumakas, Evaggelos V. Hatzikos, Ioannis P. Vlahavas
2008	A	`conf`	Reinforcement Learning with Classifier Selection for Focused Crawling. ECAI Ioannis Partalas, Georgios Paliouras, Ioannis P. Vlahavas
2007	—	`conf`	Multi-agent Reinforcement Learning Using Strategies and Voting. ICTAI (2) Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlahavas
2006	—	`conf`	Ensemble Pruning Using Reinforcement Learning. SETN Ioannis Partalas, Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas