Ioannis Partalas

发表

A Study on Greedy Algorithms for Ensemble Pruning

Grigorios Tsoumakas, I. Vlahavas, Ioannis Partalas, 2012 .

Ensemble Selection for Water Quality Prediction

Ioannis Partalas, Evaggelos V. Hatzikos, Ioannis Partalas, 2007 .

On power law distributions in large-scale taxonomies

Ioannis Partalas, Massih-Reza Amini, Rohit Babbar, 2014, SKDD.

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

Georgios Balikas, Ioannis Partalas, Axel-Cyrille Ngonga Ngomo, 2015, BMC Bioinformatics.

Ensemble Pruning Using Reinforcement Learning

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2006, SETN.

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

Bikash Joshi, Ioannis Partalas, Massih-Reza Amini, 2017, NIPS.

On Binary Reduction of Large-Scale Multiclass Classification Problems

Bikash Joshi, Ioannis Partalas, Massih-Reza Amini, 2015, IDA.

Multi-class to Binary reduction of Large-scale classification Problems

Bikash Joshi, Ioannis Partalas, Massih-Reza Amini, 2015 .

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

Daniel Hernández-Lobato, Ioannis Partalas, Ioannis Katakis, 2015, Neurocomputing.

LSHTC: A Benchmark for Large-Scale Text Classification pdf

Georgios Paliouras, Ioannis Partalas, Massih-Reza Amini, 2015, ArXiv.

Pruning an ensemble of classifiers via reinforcement learning

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2009, Neurocomputing.

Transfer Learning in Multi-Agent Reinforcement Learning Domains

Ioannis P. Vlahavas, Ioannis Partalas, Georgios Boutsioukis, 2011, EWRL.

On Flat versus Hierarchical Classification in Large-Scale Taxonomies

Ioannis Partalas, Massih-Reza Amini, Rohit Babbar, 2013, NIPS.

Reinforcement Learning and Automated Planning: A Survey

Ioannis Vlahavas, Ioannis Partalas, Dimitris Vrakas, 2008 .

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

Georgios Paliouras, Ioannis Partalas, Éric Gaussier, 2013, Data Mining and Knowledge Discovery.

Learning Taxonomy Adaptation in Large-scale Classification

Ioannis Partalas, Massih-Reza Amini, Rohit Babbar, 2016, J. Mach. Learn. Res..

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

Georgios Balikas, Georgios Paliouras, Ioannis Partalas, 2014, CLEF.

Results of the First BioASQ Workshop

Ioannis Partalas, Axel-Cyrille Ngonga Ngomo, Éric Gaussier, 2013, BioASQ@CLEF.

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

Damien Nouvel, Cédric Lopez, Ioannis Partalas, 2017, AI4KM@IJCAI.

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

Ioannis Partalas, Massih-Reza Amini, Rohit Babbar, 2013, ICONIP.

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

Daisy Zhe Wang, Ioannis Partalas, Shervin Minaee, 2019, ArXiv.

An ensemble uncertainty aware measure for directed hill climbing ensemble pruning

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2010, Machine Learning.

An Ensemble Pruning Primer

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2009, Applications of Supervised and Unsupervised Ensemble Methods.

Wasserstein distances for evaluating cross-lingual embeddings pdf

Georgios Balikas, Ioannis Partalas, Ioannis Partalas, 2019, ArXiv.

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

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2008, Inf. Sci..

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

Brooke Cowan, Shervin Minaee, A. Sadeghian, 2021 .

Transferring experience in reinforcement learning through task decomposition

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2009, AAMAS.

A Hybrid Multiagent Reinforcement Learning Approach Using Strategies and Fusion

Ioannis P. Vlahavas, Ioannis Partalas, Ioannis Feneris, 2008, Int. J. Artif. Intell. Tools.

Reinforcement Learning with Classifier Selection for Focused Crawling

Ioannis P. Vlahavas, Georgios Paliouras, Ioannis Partalas, 2008, ECAI.

Comparative Classifier Evaluation for Web-Scale Taxonomies Using Power Law

Ioannis Partalas, Massih-Reza Amini, Rohit Babbar, 2013, ESWC.

Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data

Georgios Balikas, Ioannis Partalas, Massih-Reza Amini, 2015, IDA.

Juggler: Multi-Stakeholder Ranking with Meta-Learning

Ioannis Partalas, Tiago Cunha, Phong Nguyen, 2021, MORS@RecSys.

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

Cédric Lopez, Ioannis Partalas, Frédérique Segond, 2016, JEPTALNRECITAL.