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2020 – today
- 2025
[j58]Tatiana Passali
, Thanassis Mavropoulos, Grigorios Tsoumakas, Georgios Meditskos, Stefanos Vrochidis:
Artificial disfluency detection, uh no, disfluency generation for the masses. Comput. Speech Lang. 89: 101711 (2025)- [j57]Bin Liu, Ao Zhou, Bingkun Wei, Jin Wang, Grigorios Tsoumakas:
Oversampling multi-label data based on natural neighbor and label correlation. Expert Syst. Appl. 259: 125257 (2025) - 2024
- [j56]Alexios Gidiotis, Grigorios Tsoumakas:
Bayesian active summarization. Comput. Speech Lang. 83: 101553 (2024) - [j55]Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas:
An attention matrix for every decision: faithfulness-based arbitration among multiple attention-based interpretations of transformers in text classification. Data Min. Knowl. Discov. 38(1): 128-153 (2024) - [j54]Nikolaos Mylonas, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Exploring local interpretability in dimensionality reduction: Analysis and use cases. Expert Syst. Appl. 252: 124074 (2024) - [j53]Dimitris Dimitriadis, Grigorios Tsoumakas:
Artificial fine-tuning tasks for yes/no question answering. Nat. Lang. Eng. 30(1): 73-95 (2024) - [c82]Loukritia Stefanou, Tatiana Passali, Grigorios Tsoumakas:
AUTH at BioLaySumm 2024: Bringing Scientific Content to Kids. BioNLP@ACL 2024: 793-803 - [c81]Tatiana Passali, Grigorios Tsoumakas:
Topic-Controllable Summarization: Topic-Aware Evaluation and Transformer Methods. LREC/COLING 2024: 16282-16292 - [c80]Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras:
Zero-Shot Relabeling of Weak Labels for Fine-Grained Semantic Indexing of Biomedical Literature. ECAI 2024: 2178-2185 - [c79]Ao Zhou, Bin Liu, Zhaoyang Peng, Jin Wang, Grigorios Tsoumakas:
Multi-label Adaptive Batch Selection by Highlighting Hard and Imbalanced Samples. ECML/PKDD (5) 2024: 265-281 - [i49]Ao Zhou, Bin Liu, Jin Wang, Grigorios Tsoumakas:
Multi-Label Adaptive Batch Selection by Highlighting Hard and Imbalanced Samples. CoRR abs/2403.18192 (2024) - 2023
- [j52]Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
LioNets: a neural-specific local interpretation technique exploiting penultimate layer information. Appl. Intell. 53(3): 2538-2563 (2023) - [j51]Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Truthful meta-explanations for local interpretability of machine learning models. Appl. Intell. 53(22): 26927-26948 (2023) - [j50]Dimitris Dimitriadis, Grigorios Tsoumakas:
Enhancing yes/no question answering with weak supervision via extractive question answering. Appl. Intell. 53(22): 27560-27570 (2023) - [j49]Nikolaos Mylonas, Stamatis Karlos, Grigorios Tsoumakas:
WeakMeSH: Leveraging provenance information for weakly supervised classification of biomedical articles with emerging MeSH descriptors. Artif. Intell. Medicine 137: 102505 (2023) - [j48]Bin Liu, Jin Wang, Kaiwei Sun, Grigorios Tsoumakas:
Fine-grained selective similarity integration for drug-target interaction prediction. Briefings Bioinform. 24(2) (2023) - [j47]Georgios Kamtziridis, Dimitris Vrakas, Grigorios Tsoumakas:
Does noise affect housing prices? A case study in the urban area of Thessaloniki. EPJ Data Sci. 12(1): 50 (2023) - [j46]Nikolaos Mylonas, Ioannis Mollas, Bin Liu, Yannis Manolopoulos, Grigorios Tsoumakas:
On the Persistence of Multilabel Learning, Its Recent Trends, and Its Open Issues. IEEE Intell. Syst. 38(2): 28-31 (2023) - [j45]Anastasios Nentidis, Thomas Chatzopoulos, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras:
Large-scale investigation of weakly-supervised deep learning for the fine-grained semantic indexing of biomedical literature. J. Biomed. Informatics 146: 104499 (2023) - [c78]Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas:
Beyond Annual Revisions: A Multi-Label Concept Drift Analysis of MeSH. CBMS 2023: 157-162 - [c77]Dimitrios Akrivousis, Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas:
Text classification is keyphrase explainable! Exploring local interpretability of transformer models with keyphrase extraction. DSAA 2023: 1-9 - [c76]Loukia Avramelou, Nikolaos Passalis, Grigorios Tsoumakas, Anastasios Tefas:
Domain-Specific Large Language Model Finetuning using a Model Assistant for Financial Text Summarization. SSCI 2023: 381-386 - [e8]Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13713, Springer 2023, ISBN 978-3-031-26386-6 [contents] - [e7]Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13714, Springer 2023, ISBN 978-3-031-26389-7 [contents] - [e6]Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part III. Lecture Notes in Computer Science 13715, Springer 2023, ISBN 978-3-031-26408-5 [contents] - [e5]Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part IV. Lecture Notes in Computer Science 13716, Springer 2023, ISBN 978-3-031-26411-5 [contents] - [e4]Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part V. Lecture Notes in Computer Science 13717, Springer 2023, ISBN 978-3-031-26418-4 [contents] - [e3]Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part VI. Lecture Notes in Computer Science 13718, Springer 2023, ISBN 978-3-031-26421-4 [contents] - [i48]Anastasios Nentidis, Thomas Chatzopoulos, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras:
Large-scale fine-grained semantic indexing of biomedical literature based on weakly-supervised deep learning. CoRR abs/2301.09350 (2023) - [i47]Georgios Kamtziridis, Dimitris Vrakas, Grigorios Tsoumakas:
Does Noise Affect Housing Prices? A Case Study in the Urban Area of Thessaloniki. CoRR abs/2302.13034 (2023) - [i46]Avraam Bardos, Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas:
Local Interpretability of Random Forests for Multi-Target Regression. CoRR abs/2303.16506 (2023) - [i45]Tatiana Passali, Efstathios Chatzikyriakidis, Stelios Andreadis, Thanos G. Stavropoulos, Anastasia Matonaki, Anestis Fachantidis, Grigorios Tsoumakas:
From Lengthy to Lucid: A Systematic Literature Review on NLP Techniques for Taming Long Sentences. CoRR abs/2312.05172 (2023) - 2022
- [j44]Bin Liu, Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas:
Drug-target interaction prediction via an ensemble of weighted nearest neighbors with interaction recovery. Appl. Intell. 52(4): 3705-3727 (2022) - [j43]Bin Liu, Dimitrios Papadopoulos, Fragkiskos D. Malliaros, Grigorios Tsoumakas, Apostolos N. Papadopoulos:
Multiple similarity drug-target interaction prediction with random walks and matrix factorization. Briefings Bioinform. 23(5) (2022) - [j42]Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Conclusive local interpretation rules for random forests. Data Min. Knowl. Discov. 36(4): 1521-1574 (2022) - [j41]Bin Liu, Konstantinos Blekas, Grigorios Tsoumakas:
Multi-label sampling based on local label imbalance. Pattern Recognit. 122: 108294 (2022) - [c75]Alexios Gidiotis, Grigorios Tsoumakas:
Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue. ACL (Findings) 2022: 4119-4131 - [c74]Tatiana Passali, Thanassis Mavropoulos, Grigorios Tsoumakas, Georgios Meditskos, Stefanos Vrochidis:
LARD: Large-scale Artificial Disfluency Generation. LREC 2022: 2327-2336 - [c73]Nikolaos Mylonas, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Local Multi-label Explanations for Random Forest. PKDD/ECML Workshops (1) 2022: 369-384 - [c72]Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Altruist: Argumentative Explanations through Local Interpretations of Predictive Models. SETN 2022: 21:1-21:10 - [c71]Avraam Bardos, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Local Explanation of Dimensionality Reduction. SETN 2022: 29:1-29:9 - [c70]Eleni Partalidou, Despina Christou, Grigorios Tsoumakas:
Improving Zero-Shot Entity Retrieval through Effective Dense Representations. SETN 2022: 30:1-30:5 - [c69]Eleftherios Kouloumpris, Athina Konstantinou, Stamatis Karlos, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Short-term Load Forecasting With Clustered Hybrid Models Based On Hour Granularity. SETN 2022: 42:1-42:10 - [i44]Tatiana Passali, Thanassis Mavropoulos, Grigorios Tsoumakas, George Meditskos, Stefanos Vrochidis:
LARD: Large-scale Artificial Disfluency Generation. CoRR abs/2201.05041 (2022) - [i43]Bin Liu, Dimitrios Papadopoulos, Fragkiskos D. Malliaros, Grigorios Tsoumakas, Apostolos N. Papadopoulos:
Multiple Similarity Drug-Target Interaction Prediction with Random Walks and Matrix Factorization. CoRR abs/2201.09508 (2022) - [i42]Avraam Bardos, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Local Explanation of Dimensionality Reduction. CoRR abs/2204.14012 (2022) - [i41]Tatiana Passali, Grigorios Tsoumakas:
Topic-Aware Evaluation and Transformer Methods for Topic-Controllable Summarization. CoRR abs/2206.04317 (2022) - [i40]Nikolaos Mylonas, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Local Multi-Label Explanations for Random Forest. CoRR abs/2207.01994 (2022) - [i39]Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas:
Improving Attention-Based Interpretability of Text Classification Transformers. CoRR abs/2209.10876 (2022) - [i38]Tatiana Passali, Thanassis Mavropoulos, Grigorios Tsoumakas, George Meditskos, Stefanos Vrochidis:
Artificial Disfluency Detection, Uh No, Disfluency Generation for the Masses. CoRR abs/2211.09235 (2022) - [i37]Bin Liu, Jin Wang, Kaiwei Sun, Grigorios Tsoumakas:
Fine-Grained Selective Similarity Integration for Drug-Target Interaction Prediction. CoRR abs/2212.00543 (2022) - [i36]Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Truthful Meta-Explanations for Local Interpretability of Machine Learning Models. CoRR abs/2212.03513 (2022) - 2021
- [j40]Despina Christou, Grigorios Tsoumakas:
Improving Distantly-Supervised Relation Extraction Through BERT-Based Label and Instance Embeddings. IEEE Access 9: 62574-62582 (2021) - [j39]Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras:
What is all this new MeSH about? Int. J. Digit. Libr. 22(4): 319-337 (2021) - [j38]Stamatis Karlos, Nikolaos Mylonas, Grigorios Tsoumakas:
Instance-Based Zero-Shot learning for semi-Automatic MeSH indexing. Pattern Recognit. Lett. 151: 62-68 (2021) - [j37]Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas:
Predicting Drug-Target Interactions With Multi-Label Classification and Label Partitioning. IEEE ACM Trans. Comput. Biol. Bioinform. 18(4): 1596-1607 (2021) - [c68]Nikolaos Mylonas, Stamatis Karlos, Grigorios Tsoumakas:
A Multi-instance Multi-label Weakly Supervised Approach for Dealing with Emerging MeSH Descriptors. AIME 2021: 397-407 - [c67]Argyrios S. Vartholomaios, Stamatis Karlos, Eleftherios Kouloumpris, Grigorios Tsoumakas:
Short-Term Renewable Energy Forecasting in Greece Using Prophet Decomposition and Tree-Based Ensembles. DEXA Workshops 2021: 227-238 - [c66]Spyridon Paraschos, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance. IJCAI 2021: 5004-5007 - [i35]Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras:
What is all this new MeSH about? Exploring the semantic provenance of new descriptors in the MeSH thesaurus. CoRR abs/2101.08293 (2021) - [i34]Despina Christou, Grigorios Tsoumakas:
Improving Distantly-Supervised Relation Extraction through BERT-based Label & Instance Embeddings. CoRR abs/2102.01156 (2021) - [i33]Eleni Partalidou, Despina Christou, Grigorios Tsoumakas:
Improving Zero-Shot Entity Retrieval through Effective Dense Representations. CoRR abs/2103.04156 (2021) - [i32]Spyridon Paraschos, Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance. CoRR abs/2103.17003 (2021) - [i31]Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Conclusive Local Interpretation Rules for Random Forests. CoRR abs/2104.06040 (2021) - [i30]Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer Information. CoRR abs/2104.06057 (2021) - [i29]Bin Liu, Grigorios Tsoumakas:
Optimizing Area Under the Curve Measures via Matrix Factorization for Drug-Target Interaction Prediction. CoRR abs/2105.01545 (2021) - [i28]Athanasios Lagopoulos, Grigorios Tsoumakas:
Self-citation Analysis using Sentence Embeddings. CoRR abs/2105.05527 (2021) - [i27]Alexios Gidiotis, Grigorios Tsoumakas:
Uncertainty-Aware Abstractive Summarization. CoRR abs/2105.10155 (2021) - [i26]Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras:
Harvesting the Public MeSH Note field. CoRR abs/2106.00302 (2021) - [i25]Argyrios S. Vartholomaios, Stamatis Karlos, Eleftherios Kouloumpris, Grigorios Tsoumakas:
Short-term Renewable Energy Forecasting in Greece using Prophet Decomposition and Tree-based Ensembles. CoRR abs/2107.03825 (2021) - [i24]Alexios Gidiotis, Grigorios Tsoumakas:
Bayesian Active Summarization. CoRR abs/2110.04480 (2021) - 2020
- [j36]Athanasios Lagopoulos, Grigorios Tsoumakas:
Content-aware web robot detection. Appl. Intell. 50(11): 4017-4028 (2020) - [j35]Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras:
Beyond MeSH: Fine-grained semantic indexing of biomedical literature based on weak supervision. Inf. Process. Manag. 57(5): 102282 (2020) - [j34]Bin Liu, Grigorios Tsoumakas:
Dealing with class imbalance in classifier chains via random undersampling. Knowl. Based Syst. 192: 105292 (2020) - [j33]Alexios Gidiotis, Grigorios Tsoumakas:
A Divide-and-Conquer Approach to the Summarization of Long Documents. IEEE ACM Trans. Audio Speech Lang. Process. 28: 3029-3040 (2020) - [j32]Eirini Papagiannopoulou, Grigorios Tsoumakas:
A review of keyphrase extraction. WIREs Data Mining Knowl. Discov. 10(2) (2020) - [c65]Ioannis Mollas, Nick Bassiliades, Ioannis P. Vlahavas, Grigorios Tsoumakas:
LionForests: local interpretation of random forests. NeHuAI@ECAI 2020: 17-24 - [c64]Alexios Gidiotis, Stefanos Stefanidis, Grigorios Tsoumakas:
AUTH @ CLSciSumm 20, LaySumm 20, LongSumm 20. SDP@EMNLP 2020: 251-260 - [c63]Vasileios Barzokas, Eirini Papagiannopoulou, Grigorios Tsoumakas:
Studying the Evolution of Greek Words via Word Embeddings. SETN 2020: 118-124 - [c62]Nikolaos Mylonas, Stamatis Karlos, Grigorios Tsoumakas:
Zero-Shot Classification of Biomedical Articles with Emerging MeSH Descriptors. SETN 2020: 175-184 - [e2]Annalisa Appice, Grigorios Tsoumakas, Yannis Manolopoulos, Stan Matwin:
Discovery Science - 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19-21, 2020, Proceedings. Lecture Notes in Computer Science 12323, Springer 2020, ISBN 978-3-030-61526-0 [contents] - [i23]Alexios Gidiotis, Grigorios Tsoumakas:
A Divide-and-Conquer Approach to the Summarization of Academic Articles. CoRR abs/2004.06190 (2020) - [i22]Bin Liu, Konstantinos Blekas, Grigorios Tsoumakas:
Multi-Label Sampling based on Local Label Imbalance. CoRR abs/2005.03240 (2020) - [i21]Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras:
Beyond MeSH: Fine-Grained Semantic Indexing of Biomedical Literature based on Weak Supervision. CoRR abs/2005.07638 (2020) - [i20]Ioannis Mollas, Zoe Chrysopoulou, Stamatis Karlos, Grigorios Tsoumakas:
ETHOS: an Online Hate Speech Detection Dataset. CoRR abs/2006.08328 (2020) - [i19]Eirini Papagiannopoulou, Grigorios Tsoumakas, Apostolos N. Papadopoulos:
Keywords lie far from the mean of all words in local vector space. CoRR abs/2008.09513 (2020) - [i18]Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas:
Altruist: Argumentative Explanations through Local Interpretations of Predictive Models. CoRR abs/2010.07650 (2020) - [i17]Athanasios Lagopoulos, Grigorios Tsoumakas:
From Protocol to Screening: A Hybrid Learning Approach for Technology-Assisted Systematic Literature Reviews. CoRR abs/2011.09752 (2020) - [i16]Bin Liu, Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas:
Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction Recovery. CoRR abs/2012.12325 (2020)
2010 – 2019
- 2019
- [j31]Grigorios Tsoumakas:
A survey of machine learning techniques for food sales prediction. Artif. Intell. Rev. 52(1): 441-447 (2019) - [j30]Everton Alvares Cherman, Yannis Papanikolaou, Grigorios Tsoumakas, Maria Carolina Monard:
Multi-label active learning: key issues and a novel query strategy. Evol. Syst. 10(1): 63-78 (2019) - [j29]Dimitris Dimitriadis, Grigorios Tsoumakas:
Word embeddings and external resources for answer processing in biomedical factoid question answering. J. Biomed. Informatics 92 (2019) - [j28]Athanasios Lagopoulos, Nikolaos Kapraras, Vasileios Amanatiadis, Anestis Fachantidis, Grigorios Tsoumakas:
Classifying Biomedical Figures by Modality via Multi-Label Learning. IEEE J. Biomed. Health Informatics 23(6): 2230-2237 (2019) - [c61]Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras:
Beyond MeSH: Fine-Grained Semantic Indexing of Biomedical Literature Based on Weak Supervision. CBMS 2019: 180-185 - [c60]Eirini Papagiannopoulou, Grigorios Tsoumakas:
Unsupervised Keyphrase Extraction from Scientific Publications. CICLing (1) 2019: 215-229 - [c59]Bin Liu, Grigorios Tsoumakas:
Synthetic Oversampling of Multi-label Data Based on Local Label Distribution. ECML/PKDD (2) 2019: 180-193 - [c58]Ioannis Mollas, Nikolaos Bassiliades, Grigorios Tsoumakas:
LioNets: Local Interpretation of Neural Networks Through Penultimate Layer Decoding. PKDD/ECML Workshops (1) 2019: 265-276 - [c57]Alexios Gidiotis, Grigorios Tsoumakas:
Structured Summarization of Academic Publications. PKDD/ECML Workshops (2) 2019: 636-645 - [c56]Dimitris Dimitriadis, Grigorios Tsoumakas:
Yes/No Question Answering in BioASQ 2019. PKDD/ECML Workshops (2) 2019: 661-669 - [i15]Bin Liu, Grigorios Tsoumakas:
Synthetic Oversampling of Multi-Label Data based on Local Label Distribution. CoRR abs/1905.00609 (2019) - [i14]Eirini Papagiannopoulou, Grigorios Tsoumakas:
A Review of Keyphrase Extraction. CoRR abs/1905.05044 (2019) - [i13]Alexios Gidiotis, Grigorios Tsoumakas:
Structured Summarization of Academic Publications. CoRR abs/1905.07695 (2019) - [i12]Ioannis Mollas, Nikolaos Bassiliades, Grigorios Tsoumakas:
LioNets: Local Interpretation of Neural Networks through Penultimate Layer Decoding. CoRR abs/1906.06566 (2019) - [i11]Ioannis Mollas, Grigorios Tsoumakas, Nick Bassiliades:
LionForests: Local Interpretation of Random Forests through Path Selection. CoRR abs/1911.08780 (2019) - 2018
- [j27]Pavlos Delias, Athanasios Lagopoulos, Grigorios Tsoumakas, Daniela Grigori:
Using multi-target feature evaluation to discover factors that affect business process behavior. Comput. Ind. 99: 253-261 (2018) - [j26]Yannis Papanikolaou, Grigorios Tsoumakas, Ioannis Katakis:
Hierarchical partitioning of the output space in multi-label data. Data Knowl. Eng. 116: 42-60 (2018) - [j25]Eirini Papagiannopoulou, Grigorios Tsoumakas:
Local word vectors guiding keyphrase extraction. Inf. Process. Manag. 54(6): 888-902 (2018) - [c55]Bin Liu, Grigorios Tsoumakas:
Making Classifier Chains Resilient to Class Imbalance. ACML 2018: 280-295 - [c54]Athanasios Lagopoulos, Antonios Anagnostou, Adamantios Minas, Grigorios Tsoumakas:
Learning-to-Rank and Relevance Feedback for Literature Appraisal in Empirical Medicine. CLEF 2018: 52-63 - [c53]Adamantios Minas, Athanasios Lagopoulos, Grigorios Tsoumakas:
Aristotle University's Approach to the Technologically Assisted Reviews in Empirical Medicine Task of the 2018 CLEF eHealth Lab. CLEF (Working Notes) 2018 - [c52]Yannis Papanikolaou, Grigorios Tsoumakas:
Subset Labeled LDA: A Topic Model for Extreme Multi-label Classification. DaWaK 2018: 152-162 - [c51]Athanasios Lagopoulos, Grigorios Tsoumakas, Georgios Papadopoulos:
Web Robot Detection: A Semantic Approach. ICTAI 2018: 968-974 - [c50]Antonios Anagnostou, Ioannis Mollas, Grigorios Tsoumakas:
Hatebusters: A Web Application for Actively Reporting YouTube Hate Speech. IJCAI 2018: 5796-5798 - [c49]Christos Samarinas, Grigorios Tsoumakas:
WAMBy: An information retrieval approach to web-based question answering. SETN 2018: 40:1-40:8 - [i10]Bin Liu, Grigorios Tsoumakas:
Making Classifier Chains Resilient to Class Imbalance. CoRR abs/1807.11393 (2018) - [i9]Eirini Papagiannopoulou, Grigorios Tsoumakas:
Unsupervised Keyphrase Extraction Based on Outlier Detection. CoRR abs/1808.03712 (2018) - 2017
- [j24]Yannis Papanikolaou, Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis P. Vlahavas:
Large-scale online semantic indexing of biomedical articles via an ensemble of multi-label classification models. J. Biomed. Semant. 8(1): 43:1-43:13 (2017) - [j23]Yannis Papanikolaou, James R. Foulds, Timothy N. Rubin, Grigorios Tsoumakas:
Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA. J. Mach. Learn. Res. 18: 62:1-62:58 (2017) - [c48]Athanasios Lagopoulos, Anestis Fachantidis, Grigorios Tsoumakas:
Multi-label Modality Classification for Figures in Biomedical Literature. CBMS 2017: 79-84 - [c47]Antonios Anagnostou, Athanasios Lagopoulos, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Combining Inter-Review Learning-to-Rank and Intra-Review Incremental Training for Title and Abstract Screening in Systematic Reviews. CLEF (Working Notes) 2017 - [c46]Ioannis Mamalikidis, Christos Karapiperis, Lefteris Angelis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Machine Learning Methods for Customer's Payment Acceptance Prediction in an Electricity Distribution Company. PCI 2017: 6:1-6:2 - [i8]Yannis Papanikolaou, Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis P. Vlahavas:
Large-Scale Online Semantic Indexing of Biomedical Articles via an Ensemble of Multi-Label Classification Models. CoRR abs/1704.05271 (2017) - [i7]Yannis Papanikolaou, Grigorios Tsoumakas:
Subset Labeled LDA for Large-Scale Multi-Label Classification. CoRR abs/1709.05480 (2017) - [i6]Eirini Papagiannopoulou, Grigorios Tsoumakas:
Local Word Vectors Guide Keyphrase Extraction. CoRR abs/1710.07503 (2017) - [i5]Athanasios Lagopoulos, Grigorios Tsoumakas, Georgios Papadopoulos:
Web Robot Detection in Academic Publishing. CoRR abs/1711.05098 (2017) - 2016
- [j22]Ioannis Kavakiotis, Aliki Xochelli, Andreas Agathangelidis, Grigorios Tsoumakas, Nicos Maglaveras, Kostas Stamatopoulos, Anastasia Hadzidimitriou, Ioannis P. Vlahavas, Ioanna Chouvarda:
Integrating multiple immunogenetic data sources for feature extraction and mining somatic hypermutation patterns: the case of "towards analysis" in chronic lymphocytic leukaemia. BMC Bioinform. 17(S-5): 173 (2016) - [j21]Newton Spolaôr, Maria Carolina Monard, Grigorios Tsoumakas, Huei Diana Lee:
A systematic review of multi-label feature selection and a new method based on label construction. Neurocomputing 180: 3-15 (2016) - [j20]Eleftherios Spyromitros Xioufis, Grigorios Tsoumakas, William Groves, Ioannis P. Vlahavas:
Multi-target regression via input space expansion: treating targets as inputs. Mach. Learn. 104(1): 55-98 (2016) - [c45]Everton Alvares Cherman, Grigorios Tsoumakas, Maria Carolina Monard:
Active Learning Algorithms for Multi-label Data. AIAI 2016: 267-279 - [c44]Konstantina Karponi, Grigorios Tsoumakas:
An Empirical Comparison of Methods for Multi-label Data Stream Classification. INNS Conference on Big Data 2016: 151-159 - [c43]Ioannis Kavakiotis, Alexandros Triantafyllidis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Ensemble Feature Selection using Rank Aggregation Methods for Population Genomic Data. SETN 2016: 22:1-22:4 - [c42]Anestis Fachantidis, Athanasios Tsiaras, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Segmento: An R-based Visualization-rich System for Customer Segmentation and Targeting. SETN 2016: 23:1-23:4 - [i4]Yannis Papanikolaou, Ioannis Katakis, Grigorios Tsoumakas:
Hierarchical Partitioning of the Output Space in Multi-label Data. CoRR abs/1612.06083 (2016) - 2015
- [j19]Fotini Markatopoulou, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Dynamic ensemble pruning based on multi-label classification. Neurocomputing 150: 501-512 (2015) - [c41]Yannis Papanikolaou, Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis P. Vlahavas:
AUTH-Atypon at BioASQ 3: Large-Scale Semantic Indexing in Biomedicine. CLEF (Working Notes) 2015 - [c40]Eirini Papagiannopoulou, Grigorios Tsoumakas, Nick Bassiliades:
On Discovering Deterministic Relationships in Multi-Label Learning via Linked Open Data. KNOW@LOD 2015 - [c39]Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos:
Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning. KDD 2015: 915-924 - [c38]Patroklos Samaras, Anestis Fachantidis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
A prediction model of passenger demand using AVL and APC data from a bus fleet. Panhellenic Conference on Informatics 2015: 129-134 - 2014
- [j18]Eleftherios Spyromitros Xioufis, Symeon Papadopoulos, Yiannis Kompatsiaris, Grigorios Tsoumakas, Ioannis P. Vlahavas:
A Comprehensive Study Over VLAD and Product Quantization in Large-Scale Image Retrieval. IEEE Trans. Multim. 16(6): 1713-1728 (2014) - [c37]Newton Spolaôr, Maria Carolina Monard, Grigorios Tsoumakas, Huei Diana Lee:
Label Construction for Multi-label Feature Selection. BRACIS 2014: 247-252 - [c36]Yannis Papanikolaou, Dimitrios Dimitriadis, Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis P. Vlahavas:
Ensemble Approaches for Large-Scale Multi-Label Classification and Question Answering in Biomedicine. CLEF (Working Notes) 2014: 1348-1360 - [c35]Grigorios Tsoumakas, Eleftherios Spyromitros Xioufis, Aikaterini Vrekou, Ioannis P. Vlahavas:
Multi-target Regression via Random Linear Target Combinations. ECML/PKDD (3) 2014: 225-240 - [c34]Alexandros Arvanitidis, Anna Serafi, Athena Vakali, Grigorios Tsoumakas:
Branty: A Social Media Ranking Tool for Brands. ECML/PKDD (3) 2014: 432-435 - [c33]Ioannis Kavakiotis, Alexandros Triantafyllidis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Feature Evaluation Metrics for Population Genomic Data. SETN 2014: 436-441 - [c32]Grigorios Tsoumakas, Apostolos Papadopoulos, Weining Qian, Stavros Vologiannidis, Alexander D'yakonov, Antti Puurula, Jesse Read, Jan Svec, Stanislav Semenov:
WISE 2014 Challenge: Multi-label Classification of Print Media Articles to Topics. WISE (2) 2014: 541-548 - [i3]Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos:
Discovering and Exploiting Entailment Relationships in Multi-Label Learning. CoRR abs/1404.4038 (2014) - [i2]Grigorios Tsoumakas, Eleftherios Spyromitros Xioufis, Aikaterini Vrekou, Ioannis P. Vlahavas:
Multi-Target Regression via Random Linear Target Combinations. CoRR abs/1404.5065 (2014) - 2013
- [j17]Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Transferring task models in Reinforcement Learning agents. Neurocomputing 107: 23-32 (2013) - [c31]Newton Spolaôr, Grigorios Tsoumakas:
Evaluating Feature Selection Methods for Multi-Label Text Classication. BioASQ@CLEF 2013 - [c30]Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis P. Vlahavas:
Large-Scale Semantic Indexing of Biomedical Publications. BioASQ@CLEF 2013 - [c29]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:
The 9th annual MLSP competition: New methods for acoustic classification of multiple simultaneous bird species in a noisy environment. MLSP 2013: 1-8 - 2012
- [j16]Grigorios Tsoumakas, Min-Ling Zhang, Zhi-Hua Zhou:
Introduction to the special issue on learning from multi-label data. Mach. Learn. 88(1-2): 1-4 (2012) - [c28]Eleftherios Spyromitros Xioufis, Symeon Papadopoulos, Ioannis Kompatsiaris, Grigorios Tsoumakas, Ioannis P. Vlahavas:
An empirical study on the combination of surf features with VLAD vectors for image search. WIAMIS 2012: 1-4 - [i1]Eleftherios Spyromitros Xioufis, William Groves, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Multi-Label Classification Methods for Multi-Target Regression. CoRR abs/1211.6581 (2012) - 2011
- [j15]Konstantinos Trohidis, Grigorios Tsoumakas, George Kalliris, Ioannis P. Vlahavas:
Multi-label classification of music by emotion. EURASIP J. Audio Speech Music. Process. 2011: 4 (2011) - [j14]Grigorios Tsoumakas, Eleftherios Spyromitros Xioufis, Jozef Vilcek, Ioannis P. Vlahavas:
MULAN: A Java Library for Multi-Label Learning. J. Mach. Learn. Res. 12: 2411-2414 (2011) - [j13]Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas:
Random k-Labelsets for Multilabel Classification. IEEE Trans. Knowl. Data Eng. 23(7): 1079-1089 (2011) - [c27]Eleftherios Spyromitros Xioufis, Konstantinos Sechidis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
MLKD's Participation at the CLEF 2011 Photo Annotation and Concept-Based Retrieval Tasks. CLEF (Notebook Papers/Labs/Workshop) 2011 - [c26]Anestis Fachantidis, Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Transferring Models in Hybrid Reinforcement Learning Agents. EANN/AIAI (1) 2011: 162-171 - [c25]Eleftherios Spyromitros Xioufis, Myra Spiliopoulou, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Dealing with Concept Drift and Class Imbalance in Multi-Label Stream Classification. IJCAI 2011: 1583-1588 - [c24]Eleftherios Spyromitros Xioufis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Multi-label Learning Approaches for Music Instrument Recognition. ISMIS 2011: 734-743 - [c23]Konstantinos Sechidis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
On the Stratification of Multi-label Data. ECML/PKDD (3) 2011: 145-158 - 2010
- [j12]Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Tracking recurring contexts using ensemble classifiers: an application to email filtering. Knowl. Inf. Syst. 22(3): 371-391 (2010) - [j11]Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
An ensemble uncertainty aware measure for directed hill climbing ensemble pruning. Mach. Learn. 81(3): 257-282 (2010) - [c22]Gulisong Nasierding, Abbas Z. Kouzani, Grigorios Tsoumakas:
A Triple-Random Ensemble Classification Method for Mining Multi-label Data. ICDM Workshops 2010: 49-56 - [c21]Fotini Markatopoulou, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Instance-Based Ensemble Pruning via Multi-Label Classification. ICTAI (1) 2010: 401-408 - [c20]Marios Ioannou, George Sakkas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Obtaining Bipartitions from Score Vectors for Multi-Label Classification. ICTAI (1) 2010: 409-416 - [p4]Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas:
Mining Multi-label Data. Data Mining and Knowledge Discovery Handbook 2010: 667-685
2000 – 2009
- 2009
- [j10]Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Pruning an ensemble of classifiers via reinforcement learning. Neurocomputing 72(7-9): 1900-1909 (2009) - [j9]Ioannis Katakis, Grigorios Tsoumakas, Evangelos Banos, Nick Bassiliades, Ioannis P. Vlahavas:
An adaptive personalized news dissemination system. J. Intell. Inf. Syst. 32(2): 191-212 (2009) - [c19]Ioannis Partalas, Grigorios Tsoumakas, Konstantinos Tzevanidis, Ioannis P. Vlahavas:
Transferring experience in reinforcement learning through task decomposition. AAMAS (2) 2009: 1193-1194 - [c18]Anastasios Dimou, Grigorios Tsoumakas, Vasileios Mezaris, Ioannis Kompatsiaris, Ioannis P. Vlahavas:
An Empirical Study of Multi-label Learning Methods for Video Annotation. CBMI 2009: 19-24 - [c17]Ioannis Katakis, Georgios Meditskos, Grigorios Tsoumakas, Nick Bassiliades, Ioannis P. Vlahavas:
On the Combination of Textual and Semantic Descriptions for Automated Semantic Web Service Classification. AIAI 2009: 95-104 - [c16]Gulisong Nasierding, Grigorios Tsoumakas, Abbas Z. Kouzani:
Clustering Based Multi-Label Classification for Image Annotation and Retrieval. SMC 2009: 4514-4519 - [p3]Grigorios Tsoumakas, Ioannis P. Vlahavas:
Distributed Data Mining. Database Technologies: Concepts, Methodologies, Tools, and Applications 2009: 157-164 - [p2]Grigorios Tsoumakas, Ioannis Katakis:
Multi-Label Classification. Database Technologies: Concepts, Methodologies, Tools, and Applications 2009: 309-319 - [p1]Grigorios Tsoumakas, Ioannis Partalas, Ioannis P. Vlahavas:
An Ensemble Pruning Primer. Applications of Supervised and Unsupervised Ensemble Methods 2009: 1-13 - [e1]Lazaros S. Iliadis, Ilias Maglogiannis, Grigorios Tsoumakas, Ioannis P. Vlahavas, Max Bramer:
Artificial Intelligence Applications and Innovations III, Proceedings of the 5TH IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI'2009), April 23-25, 2009, Thessaloniki, Greece. IFIP Advances in Information and Communication Technology 296, Springer 2009, ISBN 978-1-4419-0220-7 [contents] - [r1]Grigorios Tsoumakas:
Distributed Data Mining. Encyclopedia of Data Warehousing and Mining 2009: 709-715 - 2008
- [j8]Stamatia Bibi, Grigorios Tsoumakas, Ioannis Stamelos, Ioannis P. Vlahavas:
Regression via Classification applied on software defect estimation. Expert Syst. Appl. 34(3): 2091-2101 (2008) - [j7]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): 3867-3879 (2008) - [j6]Evaggelos V. Hatzikos, Grigorios Tsoumakas, George Tzanis, Nick Bassiliades, Ioannis P. Vlahavas:
An empirical study on sea water quality prediction. Knowl. Based Syst. 21(6): 471-478 (2008) - [c15]Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection. ECAI 2008: 117-121 - [c14]Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
An Ensemble of Classifiers for coping with Recurring Contexts in Data Streams. ECAI 2008: 763-764 - [c13]Konstantinos Trohidis, Grigorios Tsoumakas, George Kalliris, Ioannis P. Vlahavas:
Multi-Label Classification of Music into Emotions. ISMIR 2008: 325-330 - [c12]Eleftherios Spyromitros Xioufis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
An Empirical Study of Lazy Multilabel Classification Algorithms. SETN 2008: 401-406 - 2007
- [j5]Grigorios Tsoumakas, Ioannis P. Vlahavas:
An interoperable and scalable Web-based system for classifier sharing and fusion. Expert Syst. Appl. 33(3): 716-724 (2007) - [j4]Grigorios Tsoumakas, Ioannis Katakis:
Multi-Label Classification: An Overview. Int. J. Data Warehous. Min. 3(3): 1-13 (2007) - [c11]Grigorios Tsoumakas, Ioannis P. Vlahavas:
Random k -Labelsets: An Ensemble Method for Multilabel Classification. ECML 2007: 406-417 - 2006
- [c10]Stamatia Bibi, Grigorios Tsoumakas, Ioannis Stamelos, Ioannis P. Vlahavas:
Software Defect Prediction Using Regression via Classification. AICCSA 2006: 330-336 - [c9]Evangelos Banos, Ioannis Katakis, Nick Bassiliades, Grigorios Tsoumakas, Ioannis P. Vlahavas:
PersoNews: A Personalized News Reader Enhanced by Machine Learning and Semantic Filtering. OTM Conferences (1) 2006: 975-982 - [c8]Ioannis Partalas, Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas:
Ensemble Pruning Using Reinforcement Learning. SETN 2006: 301-310 - 2005
- [b1]Grigorios Tsoumakas:
Μηχανική μάθηση για το συγκερασμό πολλαπλών, κατανεμημένων ευφυών συστημάτων. Aristotle University Of Thessaloniki, Greece, 2005 - [j3]Dimitris Vrakas, Grigorios Tsoumakas, Nick Bassiliades, Ioannis P. Vlahavas:
HAPRC: an automatically configurable planning system. AI Commun. 18(1): 41-60 (2005) - [j2]Grigorios Tsoumakas, Lefteris Angelis, Ioannis P. Vlahavas:
Selective fusion of heterogeneous classifiers. Intell. Data Anal. 9(6): 511-525 (2005) - [c7]Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. Vlahavas:
On the Utility of Incremental Feature Selection for the Classification of Textual Data Streams. Panhellenic Conference on Informatics 2005: 338-348 - [c6]Sotiris Diplaris, Grigorios Tsoumakas, Pericles A. Mitkas, Ioannis P. Vlahavas:
Protein Classification with Multiple Algorithms. Panhellenic Conference on Informatics 2005: 448-456 - 2004
- [j1]Grigorios Tsoumakas, Lefteris Angelis, Ioannis P. Vlahavas:
Clustering classifiers for knowledge discovery from physically distributed databases. Data Knowl. Eng. 49(3): 223-242 (2004) - [c5]Grigorios Tsoumakas, Dimitris Vrakas, Nick Bassiliades, Ioannis P. Vlahavas:
Lazy Adaptive Multicriteria Planning. ECAI 2004: 693-697 - [c4]Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas:
Effective Voting of Heterogeneous Classifiers. ECML 2004: 465-476 - [c3]Grigorios Tsoumakas, Dimitris Vrakas, Nick Bassiliades, Ioannis P. Vlahavas:
Using the k-Nearest Problems for Adaptive Multicriteria Planning. SETN 2004: 132-141 - 2003
- [c2]Dimitris Vrakas, Grigorios Tsoumakas, Nick Bassiliades, Ioannis P. Vlahavas:
Learning Rules for Adaptive Planning. ICAPS 2003: 82-91 - 2002
- [c1]Grigorios Tsoumakas, Ioannis P. Vlahavas:
Effective Stacking of Distributed Classifiers. ECAI 2002: 340-344
Coauthor Index
Nick Bassiliades
aka: Nikolaos Bassiliades
aka: Nikolaos Bassiliades
[c69] [c65] [j24] [c47] [c46] [i8] [j22] [j20] [c43] [c42] [j19] [c41] [c38] [j18] [c36] [c35] [c33] [i2] [j17] [c30] [c28] [i1] [j15] [j14] [j13] [c27] [c26] [c25] [c24] [c23] [j12] [j11] [c21] [c20] [p4] [j10] [j9] [c19] [c18] [c17] [p3] [p1] [e1] [j8] [j7] [j6] [c15] [c14] [c13] [c12] [j5] [c11] [c10] [c9] [c8] [j3] [j2] [c7] [c6] [j1] [c5] [c4] [c3] [c2] [c1]
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