Grigorios Tsoumakas

According to our database, Grigorios Tsoumakas authored at least 162 papers between 2002 and 2024.

Collaborative distances:

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

2024

Artificial fine-tuning tasks for yes/no question answering.

Dimitris Dimitriadis, Grigorios Tsoumakas

Nat. Lang. Eng., January, 2024

An attention matrix for every decision: faithfulness-based arbitration among multiple attention-based interpretations of transformers in text classification.

Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas

Data Min. Knowl. Discov., January, 2024

Bayesian active summarization.

Alexios Gidiotis, Grigorios Tsoumakas

Comput. Speech Lang., January, 2024

Multi-Label Adaptive Batch Selection by Highlighting Hard and Imbalanced Samples.

Ao Zhou, Bin Liu, Jin Wang, Grigorios Tsoumakas

CoRR, 2024

2023

Does noise affect housing prices? A case study in the urban area of Thessaloniki.

Georgios Kamtziridis, Dimitris Vrakas, Grigorios Tsoumakas

EPJ Data Sci., December, 2023

Truthful meta-explanations for local interpretability of machine learning models.

Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas

Appl. Intell., November, 2023

Enhancing yes/no question answering with weak supervision via extractive question answering.

Dimitris Dimitriadis, Grigorios Tsoumakas

Appl. Intell., November, 2023

Large-scale investigation of weakly-supervised deep learning for the fine-grained semantic indexing of biomedical literature.

Anastasios Nentidis, Thomas Chatzopoulos, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras

J. Biomed. Informatics, October, 2023

Fine-grained selective similarity integration for drug-target interaction prediction.

Bin Liu, Jin Wang, Kaiwei Sun, Grigorios Tsoumakas

Briefings Bioinform., March, 2023

WeakMeSH: Leveraging provenance information for weakly supervised classification of biomedical articles with emerging MeSH descriptors.

Nikolaos Mylonas, Stamatis Karlos, Grigorios Tsoumakas

Artif. Intell. Medicine, March, 2023

On the Persistence of Multilabel Learning, Its Recent Trends, and Its Open Issues.

Nikolaos Mylonas, Ioannis Mollas, Bin Liu, Yannis Manolopoulos, Grigorios Tsoumakas

IEEE Intell. Syst., 2023

From Lengthy to Lucid: A Systematic Literature Review on NLP Techniques for Taming Long Sentences.

Tatiana Passali, Efstathios Chatzikyriakidis, Stelios Andreadis, Thanos G. Stavropoulos, Anastasia Matonaki, Anestis Fachantidis, Grigorios Tsoumakas

CoRR, 2023

Local Interpretability of Random Forests for Multi-Target Regression.

Avraam Bardos, Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas

CoRR, 2023

Large-scale fine-grained semantic indexing of biomedical literature based on weakly-supervised deep learning.

Anastasios Nentidis, Thomas Chatzopoulos, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras

CoRR, 2023

LioNets: a neural-specific local interpretation technique exploiting penultimate layer information.

Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas

Appl. Intell., 2023

Domain-Specific Large Language Model Finetuning using a Model Assistant for Financial Text Summarization.

Loukia Avramelou, Nikolaos Passalis, Grigorios Tsoumakas, Anastasios Tefas

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Text classification is keyphrase explainable! Exploring local interpretability of transformer models with keyphrase extraction.

Dimitrios Akrivousis, Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas

Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

Beyond Annual Revisions: A Multi-Label Concept Drift Analysis of MeSH.

Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas

Proceedings of the 36th IEEE International Symposium on Computer-Based Medical Systems, 2023

2022

Multi-label sampling based on local label imbalance.

Bin Liu, Konstantinos Blekas, Grigorios Tsoumakas

Pattern Recognit., 2022

Conclusive local interpretation rules for random forests.

Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas

Data Min. Knowl. Discov., 2022

Artificial Disfluency Detection, Uh No, Disfluency Generation for the Masses.

Tatiana Passali, Thanassis Mavropoulos, Grigorios Tsoumakas, George Meditskos, Stefanos Vrochidis

CoRR, 2022

Improving Attention-Based Interpretability of Text Classification Transformers.

Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas

CoRR, 2022

Topic-Aware Evaluation and Transformer Methods for Topic-Controllable Summarization.

Tatiana Passali, Grigorios Tsoumakas

CoRR, 2022

Multiple similarity drug-target interaction prediction with random walks and matrix factorization.

Bin Liu, Dimitrios Papadopoulos, Fragkiskos D. Malliaros, Grigorios Tsoumakas, Apostolos N. Papadopoulos

Briefings Bioinform., 2022

Drug-target interaction prediction via an ensemble of weighted nearest neighbors with interaction recovery.

Bin Liu, Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas

Appl. Intell., 2022

Improving Zero-Shot Entity Retrieval through Effective Dense Representations.

Eleni Partalidou, Despina Christou, Grigorios Tsoumakas

Proceedings of the SETN 2022: 12th Hellenic Conference on Artificial Intelligence, Corfu, Greece, September 7, 2022

Altruist: Argumentative Explanations through Local Interpretations of Predictive Models.

Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas

Proceedings of the SETN 2022: 12th Hellenic Conference on Artificial Intelligence, Corfu, Greece, September 7, 2022

Short-term Load Forecasting With Clustered Hybrid Models Based On Hour Granularity.

Eleftherios Kouloumpris, Athina Konstantinou, Stamatis Karlos, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the SETN 2022: 12th Hellenic Conference on Artificial Intelligence, Corfu, Greece, September 7, 2022

Local Explanation of Dimensionality Reduction.

Avraam Bardos, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas

Proceedings of the SETN 2022: 12th Hellenic Conference on Artificial Intelligence, Corfu, Greece, September 7, 2022

Local Multi-label Explanations for Random Forest.

Nikolaos Mylonas, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022

LARD: Large-scale Artificial Disfluency Generation.

Tatiana Passali, Thanassis Mavropoulos, Grigorios Tsoumakas, Georgios Meditskos, Stefanos Vrochidis

Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue.

Alexios Gidiotis, Grigorios Tsoumakas

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Predicting Drug-Target Interactions With Multi-Label Classification and Label Partitioning.

Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas

IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Instance-Based Zero-Shot learning for semi-Automatic MeSH indexing.

Stamatis Karlos, Nikolaos Mylonas, Grigorios Tsoumakas

Pattern Recognit. Lett., 2021

What is all this new MeSH about?

Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras

Int. J. Digit. Libr., 2021

Harvesting the Public MeSH Note field.

Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras

CoRR, 2021

Uncertainty-Aware Abstractive Summarization.

Alexios Gidiotis, Grigorios Tsoumakas

CoRR, 2021

Self-citation Analysis using Sentence Embeddings.

Athanasios Lagopoulos, Grigorios Tsoumakas

CoRR, 2021

Optimizing Area Under the Curve Measures via Matrix Factorization for Drug-Target Interaction Prediction.

Bin Liu, Grigorios Tsoumakas

CoRR, 2021

Improving Distantly-Supervised Relation Extraction through BERT-based Label & Instance Embeddings.

Despina Christou, Grigorios Tsoumakas

CoRR, 2021

What is all this new MeSH about? Exploring the semantic provenance of new descriptors in the MeSH thesaurus.

Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras

CoRR, 2021

Improving Distantly-Supervised Relation Extraction Through BERT-Based Label and Instance Embeddings.

Despina Christou, Grigorios Tsoumakas

IEEE Access, 2021

VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance.

Spyridon Paraschos, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Short-Term Renewable Energy Forecasting in Greece Using Prophet Decomposition and Tree-Based Ensembles.

Argyrios S. Vartholomaios, Stamatis Karlos, Eleftherios Kouloumpris, Grigorios Tsoumakas

Proceedings of the Database and Expert Systems Applications - DEXA 2021 Workshops, 2021

A Multi-instance Multi-label Weakly Supervised Approach for Dealing with Emerging MeSH Descriptors.

Nikolaos Mylonas, Stamatis Karlos, Grigorios Tsoumakas

Proceedings of the Artificial Intelligence in Medicine, 2021

2020

A review of keyphrase extraction.

Eirini Papagiannopoulou, Grigorios Tsoumakas

WIREs Data Mining Knowl. Discov., 2020

A Divide-and-Conquer Approach to the Summarization of Long Documents.

Alexios Gidiotis, Grigorios Tsoumakas

IEEE ACM Trans. Audio Speech Lang. Process., 2020

Dealing with class imbalance in classifier chains via random undersampling.

Bin Liu, Grigorios Tsoumakas

Knowl. Based Syst., 2020

Beyond MeSH: Fine-grained semantic indexing of biomedical literature based on weak supervision.

Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras

Inf. Process. Manag., 2020

From Protocol to Screening: A Hybrid Learning Approach for Technology-Assisted Systematic Literature Reviews.

Athanasios Lagopoulos, Grigorios Tsoumakas

CoRR, 2020

Keywords lie far from the mean of all words in local vector space.

Eirini Papagiannopoulou, Grigorios Tsoumakas, Apostolos N. Papadopoulos

CoRR, 2020

ETHOS: an Online Hate Speech Detection Dataset.

Ioannis Mollas, Zoe Chrysopoulou, Stamatis Karlos, Grigorios Tsoumakas

CoRR, 2020

A Divide-and-Conquer Approach to the Summarization of Academic Articles.

Alexios Gidiotis, Grigorios Tsoumakas

CoRR, 2020

Content-aware web robot detection.

Athanasios Lagopoulos, Grigorios Tsoumakas

Appl. Intell., 2020

Zero-Shot Classification of Biomedical Articles with Emerging MeSH Descriptors.

Nikolaos Mylonas, Stamatis Karlos, Grigorios Tsoumakas

Proceedings of the SETN 2020: 11th Hellenic Conference on Artificial Intelligence, 2020

Studying the Evolution of Greek Words via Word Embeddings.

Vasileios Barzokas, Eirini Papagiannopoulou, Grigorios Tsoumakas

Proceedings of the SETN 2020: 11th Hellenic Conference on Artificial Intelligence, 2020

AUTH @ CLSciSumm 20, LaySumm 20, LongSumm 20.

Alexios Gidiotis, Stefanos Stefanidis, Grigorios Tsoumakas

Proceedings of the First Workshop on Scholarly Document Processing, 2020

LionForests: local interpretation of random forests.

Ioannis Mollas, Nick Bassiliades, Ioannis P. Vlahavas, Grigorios Tsoumakas

Proceedings of the First International Workshop on New Foundations for Human-Centered AI (NeHuAI) co-located with 24th European Conference on Artificial Intelligence (ECAI 2020), 2020

2019

Classifying Biomedical Figures by Modality via Multi-Label Learning.

Athanasios Lagopoulos, Nikolaos Kapraras, Vasileios Amanatiadis, Anestis Fachantidis, Grigorios Tsoumakas

IEEE J. Biomed. Health Informatics, 2019

Word embeddings and external resources for answer processing in biomedical factoid question answering.

Dimitris Dimitriadis, Grigorios Tsoumakas

J. Biomed. Informatics, 2019

Multi-label active learning: key issues and a novel query strategy.

Everton Alvares Cherman, Yannis Papanikolaou, Grigorios Tsoumakas, Maria Carolina Monard

Evol. Syst., 2019

LionForests: Local Interpretation of Random Forests through Path Selection.

Ioannis Mollas, Grigorios Tsoumakas, Nick Bassiliades

CoRR, 2019

A survey of machine learning techniques for food sales prediction.

Grigorios Tsoumakas

Artif. Intell. Rev., 2019

LioNets: Local Interpretation of Neural Networks Through Penultimate Layer Decoding.

Ioannis Mollas, Nikolaos Bassiliades, Grigorios Tsoumakas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Synthetic Oversampling of Multi-label Data Based on Local Label Distribution.

Bin Liu, Grigorios Tsoumakas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Structured Summarization of Academic Publications.

Alexios Gidiotis, Grigorios Tsoumakas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Yes/No Question Answering in BioASQ 2019.

Dimitris Dimitriadis, Grigorios Tsoumakas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Unsupervised Keyphrase Extraction from Scientific Publications.

Eirini Papagiannopoulou, Grigorios Tsoumakas

Proceedings of the Computational Linguistics and Intelligent Text Processing, 2019

2018

Local word vectors guiding keyphrase extraction.

Eirini Papagiannopoulou, Grigorios Tsoumakas

Inf. Process. Manag., 2018

Hierarchical partitioning of the output space in multi-label data.

Yannis Papanikolaou, Grigorios Tsoumakas, Ioannis Katakis

Data Knowl. Eng., 2018

Unsupervised Keyphrase Extraction Based on Outlier Detection.

Eirini Papagiannopoulou, Grigorios Tsoumakas

CoRR, 2018

Using multi-target feature evaluation to discover factors that affect business process behavior.

Pavlos Delias, Athanasios Lagopoulos, Grigorios Tsoumakas, Daniela Grigori

Comput. Ind., 2018

WAMBy: An information retrieval approach to web-based question answering.

Christos Samarinas, Grigorios Tsoumakas

Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 2018

Hatebusters: A Web Application for Actively Reporting YouTube Hate Speech.

Antonios Anagnostou, Ioannis Mollas, Grigorios Tsoumakas

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Web Robot Detection: A Semantic Approach.

Athanasios Lagopoulos, Grigorios Tsoumakas, Georgios Papadopoulos

Proceedings of the IEEE 30th International Conference on Tools with Artificial Intelligence, 2018

Subset Labeled LDA: A Topic Model for Extreme Multi-label Classification.

Yannis Papanikolaou, Grigorios Tsoumakas

Proceedings of the Big Data Analytics and Knowledge Discovery, 2018

Aristotle University's Approach to the Technologically Assisted Reviews in Empirical Medicine Task of the 2018 CLEF eHealth Lab.

Adamantios Minas, Athanasios Lagopoulos, Grigorios Tsoumakas

Proceedings of the Working Notes of CLEF 2018, 2018

Learning-to-Rank and Relevance Feedback for Literature Appraisal in Empirical Medicine.

Athanasios Lagopoulos, Antonios Anagnostou, Adamantios Minas, Grigorios Tsoumakas

Proceedings of the Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2018

Making Classifier Chains Resilient to Class Imbalance.

Bin Liu, Grigorios Tsoumakas

Proceedings of The 10th Asian Conference on Machine Learning, 2018

2017

Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA.

Yannis Papanikolaou, James R. Foulds, Timothy N. Rubin, Grigorios Tsoumakas

J. Mach. Learn. Res., 2017

Web Robot Detection in Academic Publishing.

Athanasios Lagopoulos, Grigorios Tsoumakas, Georgios Papadopoulos

CoRR, 2017

Local Word Vectors Guide Keyphrase Extraction.

Eirini Papagiannopoulou, Grigorios Tsoumakas

CoRR, 2017

Subset Labeled LDA for Large-Scale Multi-Label Classification.

Yannis Papanikolaou, Grigorios Tsoumakas

CoRR, 2017

Large-scale online semantic indexing of biomedical articles via an ensemble of multi-label classification models.

Yannis Papanikolaou, Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis P. Vlahavas

J. Biomed. Semant., 2017

Machine Learning Methods for Customer's Payment Acceptance Prediction in an Electricity Distribution Company.

Ioannis Mamalikidis, Christos Karapiperis, Lefteris Angelis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the 21st Pan-Hellenic Conference on Informatics, 2017

Combining Inter-Review Learning-to-Rank and Intra-Review Incremental Training for Title and Abstract Screening in Systematic Reviews.

Antonios Anagnostou, Athanasios Lagopoulos, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Working Notes of CLEF 2017, 2017

Multi-label Modality Classification for Figures in Biomedical Literature.

Athanasios Lagopoulos, Anestis Fachantidis, Grigorios Tsoumakas

Proceedings of the 30th IEEE International Symposium on Computer-Based Medical Systems, 2017

2016

Multi-target regression via input space expansion: treating targets as inputs.

Eleftherios Spyromitros Xioufis, Grigorios Tsoumakas, William Groves, Ioannis P. Vlahavas

Mach. Learn., 2016

A systematic review of multi-label feature selection and a new method based on label construction.

Newton Spolaôr, Maria Carolina Monard, Grigorios Tsoumakas, Huei Diana Lee

Neurocomputing, 2016

Integrating multiple immunogenetic data sources for feature extraction and mining somatic hypermutation patterns: the case of "towards analysis" in chronic lymphocytic leukaemia.

Ioannis Kavakiotis, Aliki Xochelli, Andreas Agathangelidis, Grigorios Tsoumakas, Nicos Maglaveras, Kostas Stamatopoulos, Anastasia Hadzidimitriou, Ioannis P. Vlahavas, Ioanna Chouvarda

BMC Bioinform., 2016

Ensemble Feature Selection using Rank Aggregation Methods for Population Genomic Data.

Ioannis Kavakiotis, Alexandros Triantafyllidis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the 9th Hellenic Conference on Artificial Intelligence, 2016

Segmento: An R-based Visualization-rich System for Customer Segmentation and Targeting.

Anestis Fachantidis, Athanasios Tsiaras, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the 9th Hellenic Conference on Artificial Intelligence, 2016

An Empirical Comparison of Methods for Multi-label Data Stream Classification.

Konstantina Karponi, Grigorios Tsoumakas

Proceedings of the Advances in Big Data, 2016

Active Learning Algorithms for Multi-label Data.

Everton Alvares Cherman, Grigorios Tsoumakas, Maria Carolina Monard

Proceedings of the Artificial Intelligence Applications and Innovations, 2016

2015

Dynamic ensemble pruning based on multi-label classification.

Fotini Markatopoulou, Grigorios Tsoumakas, Ioannis P. Vlahavas

Neurocomputing, 2015

A prediction model of passenger demand using AVL and APC data from a bus fleet.

Patroklos Samaras, Anestis Fachantidis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the 19th Panhellenic Conference on Informatics, 2015

Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning.

Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

On Discovering Deterministic Relationships in Multi-Label Learning via Linked Open Data.

Eirini Papagiannopoulou, Grigorios Tsoumakas, Nick Bassiliades

Proceedings of the 4th Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data co-located with 12th Extended Semantic Web Conference (ESWC 2015), 2015

AUTH-Atypon at BioASQ 3: Large-Scale Semantic Indexing in Biomedicine.

Yannis Papanikolaou, Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis P. Vlahavas

Proceedings of the Working Notes of CLEF 2015, 2015

2014

A Comprehensive Study Over VLAD and Product Quantization in Large-Scale Image Retrieval.

Eleftherios Spyromitros Xioufis, Symeon Papadopoulos, Yiannis Kompatsiaris, Grigorios Tsoumakas, Ioannis P. Vlahavas

IEEE Trans. Multim., 2014

Discovering and Exploiting Entailment Relationships in Multi-Label Learning.

Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos

CoRR, 2014

WISE 2014 Challenge: Multi-label Classification of Print Media Articles to Topics.

Grigorios Tsoumakas, Apostolos Papadopoulos, Weining Qian, Stavros Vologiannidis, Alexander D'yakonov, Antti Puurula, Jesse Read, Jan Svec, Stanislav Semenov

Proceedings of the Web Information Systems Engineering - WISE 2014, 2014

Feature Evaluation Metrics for Population Genomic Data.

Ioannis Kavakiotis, Alexandros Triantafyllidis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Artificial Intelligence: Methods and Applications, 2014

Multi-target Regression via Random Linear Target Combinations.

Grigorios Tsoumakas, Eleftherios Spyromitros Xioufis, Aikaterini Vrekou, Ioannis P. Vlahavas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Branty: A Social Media Ranking Tool for Brands.

Alexandros Arvanitidis, Anna Serafi, Athena Vakali, Grigorios Tsoumakas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Ensemble Approaches for Large-Scale Multi-Label Classification and Question Answering in Biomedicine.

Yannis Papanikolaou, Dimitrios Dimitriadis, Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis P. Vlahavas

Proceedings of the Working Notes for CLEF 2014 Conference, 2014

Label Construction for Multi-label Feature Selection.

Newton Spolaôr, Maria Carolina Monard, Grigorios Tsoumakas, Huei Diana Lee

Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

2013

Transferring task models in Reinforcement Learning agents.

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

Neurocomputing, 2013

The 9th annual MLSP competition: New methods for acoustic classification of multiple simultaneous bird species in a noisy environment.

Forrest Briggs, Yonghong Huang, Raviv Raich, Konstantinos Eftaxias, Zhong Lei, William Cukierski, Sarah Frey Hadley, Adam Hadley, Matthew Betts, Xiaoli Z. Fern, Jed Irvine, Lawrence Neal, Anil Thomas, Gábor Fodor, Grigorios Tsoumakas, Hong Wei Ng, Thi Ngoc Tho Nguyen, Heikki Huttunen, Pekka Ruusuvuori, Tapio Manninen, Aleksandr Diment, Tuomas Virtanen, Julien Marzat, Joseph Defretin, Dave Callender, Chris Hurlburt, Ken Larrey, Maxim Milakov

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013

Large-Scale Semantic Indexing of Biomedical Publications.

Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis P. Vlahavas

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

Evaluating Feature Selection Methods for Multi-Label Text Classication.

Newton Spolaôr, Grigorios Tsoumakas

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

2012

Introduction to the special issue on learning from multi-label data.

Grigorios Tsoumakas, Min-Ling Zhang, Zhi-Hua Zhou

Mach. Learn., 2012

Multi-Label Classification Methods for Multi-Target Regression

Eleftherios Spyromitros Xioufis, William Groves, Grigorios Tsoumakas, Ioannis P. Vlahavas

CoRR, 2012

An empirical study on the combination of surf features with VLAD vectors for image search.

Eleftherios Spyromitros Xioufis, Symeon Papadopoulos, Ioannis Kompatsiaris, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the 13th International Workshop on Image Analysis for Multimedia Interactive Services, 2012

2011

Random k-Labelsets for Multilabel Classification.

Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas

IEEE Trans. Knowl. Data Eng., 2011

MULAN: A Java Library for Multi-Label Learning.

Grigorios Tsoumakas, Eleftherios Spyromitros Xioufis, Jozef Vilcek, Ioannis P. Vlahavas

J. Mach. Learn. Res., 2011

Multi-label classification of music by emotion.

Konstantinos Trohidis, Grigorios Tsoumakas, George Kalliris, Ioannis P. Vlahavas

EURASIP J. Audio Speech Music. Process., 2011

On the Stratification of Multi-label Data.

Konstantinos Sechidis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Multi-label Learning Approaches for Music Instrument Recognition.

Eleftherios Spyromitros Xioufis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Foundations of Intelligent Systems - 19th International Symposium, 2011

Dealing with Concept Drift and Class Imbalance in Multi-Label Stream Classification.

Eleftherios Spyromitros Xioufis, Myra Spiliopoulou, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the IJCAI 2011, 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

MLKD's Participation at the CLEF 2011 Photo Annotation and Concept-Based Retrieval Tasks.

Eleftherios Spyromitros Xioufis, Konstantinos Sechidis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the CLEF 2011 Labs and Workshop, 2011

2010

Mining Multi-label Data.

Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas

Proceedings of the Data Mining and Knowledge Discovery Handbook, 2nd ed., 2010

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

Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas

Mach. Learn., 2010

Tracking recurring contexts using ensemble classifiers: an application to email filtering.

Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Knowl. Inf. Syst., 2010

Instance-Based Ensemble Pruning via Multi-Label Classification.

Fotini Markatopoulou, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010

Obtaining Bipartitions from Score Vectors for Multi-Label Classification.

Marios Ioannou, George Sakkas, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010

A Triple-Random Ensemble Classification Method for Mining Multi-label Data.

Gulisong Nasierding, Abbas Z. Kouzani, Grigorios Tsoumakas

Proceedings of the ICDMW 2010, 2010

2009

An Ensemble Pruning Primer.

Grigorios Tsoumakas, Ioannis Partalas, Ioannis P. Vlahavas

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

Distributed Data Mining.

Grigorios Tsoumakas

Proceedings of the Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes), 2009

An adaptive personalized news dissemination system.

Ioannis Katakis, Grigorios Tsoumakas, Evangelos Banos, Nick Bassiliades, Ioannis P. Vlahavas

J. Intell. Inf. Syst., 2009

Pruning an ensemble of classifiers via reinforcement learning.

Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas

Neurocomputing, 2009

Clustering Based Multi-Label Classification for Image Annotation and Retrieval.

Gulisong Nasierding, Grigorios Tsoumakas, Abbas Z. Kouzani

Proceedings of the IEEE International Conference on Systems, 2009

On the Combination of Textual and Semantic Descriptions for Automated Semantic Web Service Classification.

Ioannis Katakis, Georgios Meditskos, Grigorios Tsoumakas, Nick Bassiliades, Ioannis P. Vlahavas

Proceedings of the Artificial Intelligence Applications and Innovations III, 2009

An Empirical Study of Multi-label Learning Methods for Video Annotation.

Anastasios Dimou, Grigorios Tsoumakas, Vasileios Mezaris, Ioannis Kompatsiaris, Ioannis P. Vlahavas

Proceedings of the Seventh International Workshop on Content-Based Multimedia Indexing, 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

Distributed Data Mining.

Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Database Technologies: Concepts, 2009

Multi-Label Classification.

Grigorios Tsoumakas, Ioannis Katakis

Proceedings of the Database Technologies: Concepts, 2009

2008

An empirical study on sea water quality prediction.

Evaggelos V. Hatzikos, Grigorios Tsoumakas, George Tzanis, Nick Bassiliades, Ioannis P. Vlahavas

Knowl. Based Syst., 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

Regression via Classification applied on software defect estimation.

Stamatia Bibi, Grigorios Tsoumakas, Ioannis Stamelos, Ioannis P. Vlahavas

Expert Syst. Appl., 2008

An Empirical Study of Lazy Multilabel Classification Algorithms.

Eleftherios Spyromitros Xioufis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Artificial Intelligence: Theories, 2008

Multi-Label Classification of Music into Emotions.

Konstantinos Trohidis, Grigorios Tsoumakas, George Kalliris, Ioannis P. Vlahavas

Proceedings of the ISMIR 2008, 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

An Ensemble of Classifiers for coping with Recurring Contexts in Data Streams.

Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the ECAI 2008, 2008

2007

Multi-Label Classification: An Overview.

Grigorios Tsoumakas, Ioannis Katakis

Int. J. Data Warehous. Min., 2007

An interoperable and scalable Web-based system for classifier sharing and fusion.

Grigorios Tsoumakas, Ioannis P. Vlahavas

Expert Syst. Appl., 2007

Random <i>k</i> -Labelsets: An Ensemble Method for Multilabel Classification.

Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Machine Learning: ECML 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

PersoNews: A Personalized News Reader Enhanced by Machine Learning and Semantic Filtering.

Evangelos Banos, Ioannis Katakis, Nick Bassiliades, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the On the Move to Meaningful Internet Systems 2006: CoopIS, 2006

Software Defect Prediction Using Regression via Classification.

Stamatia Bibi, Grigorios Tsoumakas, Ioannis Stamelos, Ioannis P. Vlahavas

Proceedings of the 2006 IEEE/ACS International Conference on Computer Systems and Applications (AICCSA 2006), 2006

2005

Μηχανική μάθηση για το συγκερασμό πολλαπλών, κατανεμημένων ευφυών συστημάτων

Grigorios Tsoumakas

PhD thesis, 2005

Selective fusion of heterogeneous classifiers.

Grigorios Tsoumakas, Lefteris Angelis, Ioannis P. Vlahavas

Intell. Data Anal., 2005

HAPRC: an automatically configurable planning system.

Dimitris Vrakas, Grigorios Tsoumakas, Nick Bassiliades, Ioannis P. Vlahavas

AI Commun., 2005

On the Utility of Incremental Feature Selection for the Classification of Textual Data Streams.

Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the Advances in Informatics, 2005

Protein Classification with Multiple Algorithms.

Sotiris Diplaris, Grigorios Tsoumakas, Pericles A. Mitkas, Ioannis P. Vlahavas

Proceedings of the Advances in Informatics, 2005

2004

Clustering classifiers for knowledge discovery from physically distributed databases.

Grigorios Tsoumakas, Lefteris Angelis, Ioannis P. Vlahavas

Data Knowl. Eng., 2004

Using the k-Nearest Problems for Adaptive Multicriteria Planning.

Grigorios Tsoumakas, Dimitris Vrakas, Nick Bassiliades, Ioannis P. Vlahavas

Proceedings of the Methods and Applications of Artificial Intelligence, 2004

Effective Voting of Heterogeneous Classifiers.

Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas

Proceedings of the Machine Learning: ECML 2004, 2004

Lazy Adaptive Multicriteria Planning.

Grigorios Tsoumakas, Dimitris Vrakas, Nick Bassiliades, Ioannis P. Vlahavas

Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004

2003

Learning Rules for Adaptive Planning.

Dimitris Vrakas, Grigorios Tsoumakas, Nick Bassiliades, Ioannis P. Vlahavas

Proceedings of the Thirteenth International Conference on Automated Planning and Scheduling (ICAPS 2003), 2003

2002

Effective Stacking of Distributed Classifiers.

Grigorios Tsoumakas, Ioannis P. Vlahavas

Proceedings of the 15th European Conference on Artificial Intelligence, 2002