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ORCIDEirini Ntoutsi
Irene Ntoutsi
Person information
- affiliation: Bundeswehr University Munich, Germany
- affiliation (former): Leibniz University Hannover, Germany
- affiliation (former): L3S Research Center, Hannover, Germany
- affiliation (former): LMU Munich, Institute of Informatics, Germany
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2020 – today
- 2024
[j27]Simone Fabbrizzi
, Xuan Zhao, Emmanouil Krasanakis, Symeon Papadopoulos, Eirini Ntoutsi:
Studying bias in visual features through the lens of optimal transport. Data Min. Knowl. Discov. 38(1): 281-312 (2024)- [j26]Simone Fabbrizzi, Xuan Zhao, Emmanouil Krasanakis, Symeon Papadopoulos, Eirini Ntoutsi:
Correction to: Studying bias in visual features through the lens of optimal transport. Data Min. Knowl. Discov. 38(1): 313-314 (2024) - [c78]Yi Cai, Arthur Zimek, Eirini Ntoutsi, Gerhard Wunder:
Transparent Neighborhood Approximation for Text Classifier Explanation by Probability-Based Editing. DSAA 2024: 1-10 - [c77]Alaa Elobaid, Nathan Ramoly, Lara Younes, Symeon Papadopoulos, Eirini Ntoutsi, Ioannis Kompatsiaris:
Sum of Group Error Differences: A Critical Examination of Bias Evaluation in Biometric Verification and a Dual-Metric Measure. FG 2024: 1-9 - [c76]Arjun Roy, Christos Koutlis, Symeon Papadopoulos, Eirini Ntoutsi:
FairBranch: Mitigating Bias Transfer in Fair Multi-task Learning. IJCNN 2024: 1-8 - [c75]Siamak Ghodsi, Seyed Amjad Seyedi, Eirini Ntoutsi:
Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering. PAKDD (1) 2024: 284-296 - [c74]Vasilis Gkolemis, Theodore Dalamagas, Eirini Ntoutsi, Christos Diou:
Fast and Accurate Regional Effect Plots for Automated Tabular Data Analysis. VLDB Workshops 2024 - [e12]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14941, Springer 2024, ISBN 978-3-031-70340-9 [contents] - [e11]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14942, Springer 2024, ISBN 978-3-031-70343-0 [contents] - [e10]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part III. Lecture Notes in Computer Science 14943, Springer 2024, ISBN 978-3-031-70351-5 [contents] - [e9]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IV. Lecture Notes in Computer Science 14944, Springer 2024, ISBN 978-3-031-70358-4 [contents] - [e8]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part V. Lecture Notes in Computer Science 14945, Springer 2024, ISBN 978-3-031-70361-4 [contents] - [e7]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VI. Lecture Notes in Computer Science 14946, Springer 2024, ISBN 978-3-031-70364-5 [contents] - [e6]Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VII. Lecture Notes in Computer Science 14947, Springer 2024, ISBN 978-3-031-70367-6 [contents] - [e5]Albert Bifet, Povilas Daniusis, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Kai Puolamäki, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VIII. Lecture Notes in Computer Science 14948, Springer 2024, ISBN 978-3-031-70370-6 [contents] - [i42]Siamak Ghodsi, Seyed Amjad Seyedi, Eirini Ntoutsi:
Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering. CoRR abs/2402.10756 (2024) - [i41]Vasilis Gkolemis, Christos Diou, Eirini Ntoutsi, Theodore Dalamagas, Bernd Bischl, Julia Herbinger, Giuseppe Casalicchio:
Effector: A Python package for regional explanations. CoRR abs/2404.02629 (2024) - [i40]Alaa Elobaid, Nathan Ramoly, Lara Younes, Symeon Papadopoulos, Eirini Ntoutsi, Ioannis Kompatsiaris:
Sum of Group Error Differences: A Critical Examination of Bias Evaluation in Biometric Verification and a Dual-Metric Measure. CoRR abs/2404.15385 (2024) - [i39]Chethan Krishnamurthy Ramanaik, Arjun Roy, Eirini Ntoutsi:
Adversarial Robustness of VAEs across Intersectional Subgroups. CoRR abs/2407.03864 (2024) - [i38]Swati Swati, Arjun Roy, Eirini Ntoutsi:
Exploring Fusion Techniques in Multimodal AI-Based Recruitment: Insights from FairCVdb. CoRR abs/2407.16892 (2024) - [i37]Emmanouil Panagiotou, Arjun Roy, Eirini Ntoutsi:
Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study. CoRR abs/2409.05215 (2024) - 2023
- [j25]Vasileios Iosifidis, Symeon Papadopoulos, Bodo Rosenhahn, Eirini Ntoutsi:
AdaCC: cumulative cost-sensitive boosting for imbalanced classification. Knowl. Inf. Syst. 65(2): 789-826 (2023) - [c73]Vasilis Gkolemis, Theodore Dalamagas, Eirini Ntoutsi, Christos Diou:
RHALE: Robust and Heterogeneity-Aware Accumulated Local Effects. ECAI 2023: 859-866 - [c72]Siamak Ghodsi, Eirini Ntoutsi:
Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution Discrepancy. EWAF 2023 - [c71]Arjun Roy, Jan Horstmann, Eirini Ntoutsi:
Multi-dimensional Discrimination in Law and Machine Learning - A Comparative Overview. FAccT 2023: 89-100 - [c70]Eirini Ntoutsi:
Keynote Speech 2: Bias and Discrimination in AI Systems: From Single-Identity Dimensions to Multi-Discrimination. MCNA 2023: 2 - [c69]Tai Le Quy, Gunnar Friege, Eirini Ntoutsi:
Multi-fair Capacitated Students-Topics Grouping Problem. PAKDD (1) 2023: 507-519 - [i36]Tai Le Quy, Gunnar Friege, Eirini Ntoutsi:
A review of clustering models in educational data science towards fairness-aware learning. CoRR abs/2301.03421 (2023) - [i35]Arjun Roy, Jan Horstmann, Eirini Ntoutsi:
Multi-dimensional discrimination in Law and Machine Learning - A comparative overview. CoRR abs/2302.05995 (2023) - [i34]Yi Cai, Arthur Zimek, Eirini Ntoutsi, Gerhard Wunder:
Explaining text classifiers through progressive neighborhood approximation with realistic samples. CoRR abs/2302.07733 (2023) - [i33]Siamak Ghodsi, Eirini Ntoutsi:
Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution Discrepancy. CoRR abs/2306.01699 (2023) - [i32]Vasilis Gkolemis, Theodore Dalamagas, Eirini Ntoutsi, Christos Diou:
RHALE: Robust and Heterogeneity-aware Accumulated Local Effects. CoRR abs/2309.11193 (2023) - [i31]Vasilis Gkolemis, Anargiros Tzerefos, Theodore Dalamagas, Eirini Ntoutsi, Christos Diou:
Regionally Additive Models: Explainable-by-design models minimizing feature interactions. CoRR abs/2309.12215 (2023) - [i30]Arjun Roy, Christos Koutlis, Symeon Papadopoulos, Eirini Ntoutsi:
FairBranch: Fairness Conflict Correction on Task-group Branches for Fair Multi-Task Learning. CoRR abs/2310.13746 (2023) - [i29]Emmanouil Panagiotou, Eirini Ntoutsi:
Learning impartial policies for sequential counterfactual explanations using Deep Reinforcement Learning. CoRR abs/2311.00523 (2023) - 2022
- [j24]Simone Fabbrizzi, Symeon Papadopoulos, Eirini Ntoutsi, Ioannis Kompatsiaris:
A survey on bias in visual datasets. Comput. Vis. Image Underst. 223: 103552 (2022) - [j23]Vasileios Iosifidis, Arjun Roy, Eirini Ntoutsi:
Parity-based cumulative fairness-aware boosting. Knowl. Inf. Syst. 64(10): 2737-2770 (2022) - [j22]Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi:
A survey on datasets for fairness-aware machine learning. WIREs Data Mining Knowl. Discov. 12(3) (2022) - [c68]Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi:
Multi-fairness Under Class-Imbalance. DS 2022: 286-301 - [c67]Yi Cai, Arthur Zimek, Gerhard Wunder, Eirini Ntoutsi:
Power of Explanations: Towards automatic debiasing in hate speech detection. DSAA 2022: 1-10 - [c66]Tai Le Quy, Thi Huyen Nguyen, Gunnar Friege, Eirini Ntoutsi:
Evaluation of Group Fairness Measures in Student Performance Prediction Problems. PKDD/ECML Workshops (1) 2022: 119-136 - [c65]Arjun Roy, Eirini Ntoutsi:
Learning to Teach Fairness-Aware Deep Multi-task Learning. ECML/PKDD (1) 2022: 710-726 - [i28]Vasileios Iosifidis, Arjun Roy, Eirini Ntoutsi:
Parity-based Cumulative Fairness-aware Boosting. CoRR abs/2201.01148 (2022) - [i27]Xuejiao Tang, Tai Le Quy, Eirini Ntoutsi, Kea Turner, Vasile Palade, Israat Haque, Peng Xu, Chris Brown, Wenbin Zhang:
Attention Mechanism based Cognition-level Scene Understanding. CoRR abs/2204.08027 (2022) - [i26]Arjun Roy, Eirini Ntoutsi:
Learning to Teach Fairness-aware Deep Multi-task Learning. CoRR abs/2206.08403 (2022) - [i25]Tai Le Quy, Gunnar Friege, Eirini Ntoutsi:
Multiple Fairness and Cardinality constraints for Students-Topics Grouping Problem. CoRR abs/2206.09895 (2022) - [i24]Siamak Ghodsi, Harith Alani, Eirini Ntoutsi:
Context matters for fairness - a case study on the effect of spatial distribution shifts. CoRR abs/2206.11436 (2022) - [i23]Tai Le Quy, Thi Huyen Nguyen, Gunnar Friege, Eirini Ntoutsi:
Evaluation of group fairness measures in student performance prediction problems. CoRR abs/2208.10625 (2022) - [i22]Vasileios Iosifidis, Symeon Papadopoulos, Bodo Rosenhahn, Eirini Ntoutsi:
AdaCC: Cumulative Cost-Sensitive Boosting for Imbalanced Classification. CoRR abs/2209.08309 (2022) - [i21]Yi Cai, Arthur Zimek, Gerhard Wunder, Eirini Ntoutsi:
Power of Explanations: Towards automatic debiasing in hate speech detection. CoRR abs/2209.09975 (2022) - 2021
- [j21]Bettina Berendt, Fabien Gandon, Susan Halford, Wendy Hall, Jim Hendler, Katharina E. Kinder-Kurlanda, Eirini Ntoutsi, Steffen Staab:
Web Futures: Inclusive, Intelligent, Sustainable The 2020 Manifesto for Web Science (Dagstuhl Perspectives Workshop 18262). Dagstuhl Manifestos 9(1): 1-42 (2021) - [j20]Toon Calders, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Salvatore Ruggieri:
Introduction to The Special Section on Bias and Fairness in AI. SIGKDD Explor. 23(1): 1-3 (2021) - [c64]Yi Cai, Arthur Zimek, Eirini Ntoutsi:
XPROAX-Local explanations for text classification with progressive neighborhood approximation. DSAA 2021: 1-10 - [c63]Tai Le Quy, Eirini Ntoutsi:
Towards fair, explainable and actionable clustering for learning analytics. EDM 2021 - [c62]Tai Le Quy, Arjun Roy, Gunnar Friege, Eirini Ntoutsi:
Fair-Capacitated Clustering. EDM 2021 - [c61]Xuejiao Tang, Wenbin Zhang, Yi Yu, Kea Turner, Tyler Derr, Mengyu Wang, Eirini Ntoutsi:
Interpretable Visual Understanding with Cognitive Attention Network. ICANN (1) 2021: 555-568 - [c60]Philip Naumann, Eirini Ntoutsi:
Consequence-Aware Sequential Counterfactual Generation. ECML/PKDD (2) 2021: 682-698 - [e4]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e3]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - [i20]Tai Le Quy, Sergej Zerr, Eirini Ntoutsi, Wolfgang Nejdl:
Data augmentation for dealing with low sampling rates in NILM. CoRR abs/2104.02055 (2021) - [i19]Philip Naumann, Eirini Ntoutsi:
Consequence-aware Sequential Counterfactual Generation. CoRR abs/2104.05592 (2021) - [i18]Tai Le Quy, Arjun Roy, Gunnar Friege, Eirini Ntoutsi:
Fair-Capacitated Clustering. CoRR abs/2104.12116 (2021) - [i17]Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi:
Multi-Fair Pareto Boosting. CoRR abs/2104.13312 (2021) - [i16]Simone Fabbrizzi, Symeon Papadopoulos, Eirini Ntoutsi, Ioannis Kompatsiaris:
A Survey on Bias in Visual Datasets. CoRR abs/2107.07919 (2021) - [i15]Xuejiao Tang, Wenbin Zhang, Yi Yu, Kea Turner, Tyler Derr, Mengyu Wang, Eirini Ntoutsi:
Interpretable Visual Understanding with Cognitive Attention Network. CoRR abs/2108.02924 (2021) - [i14]Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi:
Online Fairness-Aware Learning with Imbalanced Data Streams. CoRR abs/2108.06231 (2021) - [i13]Yi Cai, Arthur Zimek, Eirini Ntoutsi:
XPROAX-Local explanations for text classification with progressive neighborhood approximation. CoRR abs/2109.15004 (2021) - [i12]Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi:
A survey on datasets for fairness-aware machine learning. CoRR abs/2110.00530 (2021) - 2020
- [j19]Christian Beyer, Vishnu Unnikrishnan, Robert Brüggemann, Vincent Toulouse, Hafez Kader Omar, Eirini Ntoutsi, Myra Spiliopoulou:
Resource management for model learning at entity level. Ann. des Télécommunications 75(9-10): 549-561 (2020) - [j18]Christian Beyer, Maik Büttner, Vishnu Unnikrishnan, Miro Schleicher, Eirini Ntoutsi, Myra Spiliopoulou:
Active feature acquisition on data streams under feature drift. Ann. des Télécommunications 75(9-10): 597-611 (2020) - [j17]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
Call for Special Issue Papers: Evaluation and Experimental Design in Data Mining and Machine Learning. Big Data 8(4): 253-254 (2020) - [j16]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
Call for Special Issue Papers: Evaluation and Experimental Design in Data Mining and Machine Learning. Big Data 8(5): 456-457 (2020) - [j15]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
Call for Special Issue Papers: Evaluation and Experimental Design in Data Mining and Machine Learning. Big Data 8(6): 546-547 (2020) - [j14]Vishnu Unnikrishnan, Christian Beyer, Pawel Matuszyk, Uli Niemann, Rüdiger Pryss, Winfried Schlee, Eirini Ntoutsi, Myra Spiliopoulou:
Entity-level stream classification: exploiting entity similarity to label the future observations referring to an entity. Int. J. Data Sci. Anal. 9(1): 1-15 (2020) - [j13]Pavlos Fafalios, Vasileios Iosifidis, Kostas Stefanidis, Eirini Ntoutsi:
Tracking the history and evolution of entities: entity-centric temporal analysis of large social media archives. Int. J. Digit. Libr. 21(1): 5-17 (2020) - [j12]Vasileios Iosifidis, Eirini Ntoutsi:
Sentiment analysis on big sparse data streams with limited labels. Knowl. Inf. Syst. 62(4): 1393-1432 (2020) - [j11]Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju, Vasileios Iosifidis, Wolfgang Nejdl, Maria-Esther Vidal, Salvatore Ruggieri, Franco Turini, Symeon Papadopoulos, Emmanouil Krasanakis, Ioannis Kompatsiaris, Katharina Kinder-Kurlanda, Claudia Wagner, Fariba Karimi, Miriam Fernández, Harith Alani, Bettina Berendt, Tina Kruegel, Christian Heinze, Klaus Broelemann, Gjergji Kasneci, Thanassis Tiropanis, Steffen Staab:
Bias in data-driven artificial intelligence systems - An introductory survey. WIREs Data Mining Knowl. Discov. 10(3) (2020) - [c59]Amir Abolfazli, Eirini Ntoutsi:
Drift-Aware Multi-Memory Model for Imbalanced Data Streams. IEEE BigData 2020: 878-885 - [c58]Bahman Askari, Tai Le Quy, Eirini Ntoutsi:
Taxi Demand Prediction using an LSTM-Based Deep Sequence Model and Points of Interest. COMPSAC 2020: 1719-1724 - [c57]Vasileios Iosifidis, Eirini Ntoutsi:
FABBOO - Online Fairness-Aware Learning Under Class Imbalance. DS 2020: 159-174 - [c56]Tongxin Hu, Vasileios Iosifidis, Wentong Liao, Hang Zhang, Michael Ying Yang, Eirini Ntoutsi, Bodo Rosenhahn:
FairNN - Conjoint Learning of Fair Representations for Fair Decisions. DS 2020: 581-595 - [c55]Eirini Ntoutsi:
Bias in AI-systems: A multi-step approach. NL4XAI@INGL 2020: 3-4 - [e2]Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla:
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6 [contents] - [i11]Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju, Vasileios Iosifidis, Wolfgang Nejdl, Maria-Esther Vidal, Salvatore Ruggieri, Franco Turini, Symeon Papadopoulos, Emmanouil Krasanakis, Ioannis Kompatsiaris, Katharina Kinder-Kurlanda, Claudia Wagner, Fariba Karimi, Miriam Fernández, Harith Alani, Bettina Berendt, Tina Kruegel, Christian Heinze, Klaus Broelemann, Gjergji Kasneci, Thanassis Tiropanis, Steffen Staab:
Bias in Data-driven AI Systems - An Introductory Survey. CoRR abs/2001.09762 (2020) - [i10]Vasileios Iosifidis, Besnik Fetahu, Eirini Ntoutsi:
FAE: A Fairness-Aware Ensemble Framework. CoRR abs/2002.00695 (2020) - [i9]Tongxin Hu, Vasileios Iosifidis, Wentong Liao, Hang Zhang, Michael Ying Yang, Eirini Ntoutsi, Bodo Rosenhahn:
FairNN- Conjoint Learning of Fair Representations for Fair Decisions. CoRR abs/2004.02173 (2020) - [i8]Amir Abolfazli, Eirini Ntoutsi:
Drift-Aware Multi-Memory Model for Imbalanced Data Streams. CoRR abs/2012.14791 (2020)
2010 – 2019
- 2019
- [c54]Vasileios Iosifidis, Besnik Fetahu, Eirini Ntoutsi:
FAE: A Fairness-Aware Ensemble Framework. IEEE BigData 2019: 1375-1380 - [c53]Vasileios Iosifidis, Eirini Ntoutsi:
AdaFair: Cumulative Fairness Adaptive Boosting. CIKM 2019: 781-790 - [c52]Vasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi:
Fairness-Enhancing Interventions in Stream Classification. DEXA (1) 2019: 261-276 - [c51]Wenbin Zhang, Eirini Ntoutsi:
FAHT: An Adaptive Fairness-aware Decision Tree Classifier. IJCAI 2019: 1480-1486 - [c50]Tai Le Quy, Wolfgang Nejdl, Myra Spiliopoulou, Eirini Ntoutsi:
A Neighborhood-Augmented LSTM Model for Taxi-Passenger Demand Prediction. MASTER@PKDD/ECML 2019: 100-116 - [c49]Christian Beyer, Vishnu Unnikrishnan, Uli Niemann, Pawel Matuszyk, Eirini Ntoutsi, Myra Spiliopoulou:
Exploiting entity information for stream classification over a stream of reviews. SAC 2019: 564-573 - [c48]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2019). EDML@SDM 2019: 1-3 - [e1]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
Proceedings of the 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning co-located with SIAM International Conference on Data Mining (SDM 2019), Calgary, Alberta, Canada, May 4th, 2019. CEUR Workshop Proceedings 2436, CEUR-WS.org 2019 [contents] - [i7]Vasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi:
Fairness-enhancing interventions in stream classification. CoRR abs/1907.07223 (2019) - [i6]Wenbin Zhang, Eirini Ntoutsi:
FAHT: An Adaptive Fairness-aware Decision Tree Classifier. CoRR abs/1907.07237 (2019) - [i5]Vasileios Iosifidis, Eirini Ntoutsi:
AdaFair: Cumulative Fairness Adaptive Boosting. CoRR abs/1909.08982 (2019) - 2018
- [j10]Stratos Mansalis, Eirini Ntoutsi, Nikos Pelekis, Yannis Theodoridis:
An evaluation of data stream clustering algorithms. Stat. Anal. Data Min. 11(4): 167-187 (2018) - [c47]Damianos P. Melidis, Myra Spiliopoulou, Eirini Ntoutsi:
Learning under Feature Drifts in Textual Streams. CIKM 2018: 527-536 - [c46]Christian Beyer, Vishnu Unnikrishnan, Pawel Matuszyk, Uli Niemann, Rüdiger Pryss, Winfried Schlee, Eirini Ntoutsi, Myra Spiliopoulou:
Entity-Level Stream Classification: Exploiting Entity Similarity to Label the Future Observations Referring to an Entity. DSAA 2018: 246-255 - [c45]Pavlos Fafalios, Vasileios Iosifidis, Eirini Ntoutsi, Stefan Dietze:
TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets. ESWC 2018: 177-190 - [c44]Christopher Blake, Eirini Ntoutsi:
Reinforcement Learning Based Decision Tree Induction Over Data Streams with Concept Drifts. ICBK 2018: 328-335 - [c43]Christian Beyer, Uli Niemann, Vishnu Unnikrishnan, Eirini Ntoutsi, Myra Spiliopoulou:
Predicting polarities of entity-centered documents without reading their contents. SAC 2018: 525-528 - [c42]Damianos P. Melidis, Alvaro Veizaga Campero, Vasileios Iosifidis, Eirini Ntoutsi, Myra Spiliopoulou:
Enriching Lexicons with Ephemeral Words for Sentiment Analysis in Social Streams. WIMS 2018: 38:1-38:8 - [r2]Kostas Stefanidis, Eirini Ntoutsi, Haridimos Kondylakis, Yannis Velegrakis:
Social-Based Collaborative Filtering. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i4]Pavlos Fafalios, Vasileios Iosifidis, Eirini Ntoutsi, Stefan Dietze:
TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets. CoRR abs/1810.10308 (2018) - [i3]Pavlos Fafalios, Vasileios Iosifidis, Kostas Stefanidis, Eirini Ntoutsi:
Tracking the History and Evolution of Entities: Entity-centric Temporal Analysis of Large Social Media Archives. CoRR abs/1810.11017 (2018) - [i2]Susan Halford, James A. Hendler, Eirini Ntoutsi, Steffen Staab:
10 Years of Web Science: Closing The Loop (Dagstuhl Perspectives Workshop 18262). Dagstuhl Reports 8(6): 173-198 (2018) - 2017
- [c41]Pavlos Fafalios, Vasileios Iosifidis, Kostas Stefanidis, Eirini Ntoutsi:
Multi-aspect Entity-Centric Analysis of Big Social Media Archives. TPDL 2017: 261-273 - [c40]Vasileios Iosifidis, Annina Oelschlager, Eirini Ntoutsi:
Sentiment Classification over Opinionated Data Streams Through Informed Model Adaptation. TPDL 2017: 369-381 - [c39]Vasileios Iosifidis, Eirini Ntoutsi:
Large Scale Sentiment Learning with Limited Labels. KDD 2017: 1823-1832 - [c38]Daniel Basaran, Eirini Ntoutsi, Arthur Zimek:
Redundancies in Data and their Effect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets. SDM 2017: 390-398 - [r1]Myra Spiliopoulou, Eirini Ntoutsi, Max Zimmermann:
Opinion Stream Mining. Encyclopedia of Machine Learning and Data Mining 2017: 938-947 - 2016
- [j9]Max Zimmermann, Eirini Ntoutsi, Myra Spiliopoulou:
Extracting opinionated (sub)features from a stream of product reviews using accumulated novelty and internal re-organization. Inf. Sci. 329: 876-899 (2016) - [c37]Markus Mauder, Eirini Ntoutsi, Peer Kröger, Christoph Mayr, Gisela Grupe, Anita Toncala, Stefan Holzl:
Applying data mining methods for the analysis of stable isotope data in bioarchaeology. eScience 2016: 233-242 - [c36]Kostas Stefanidis, Eirini Ntoutsi:
Cluster-based Contextual Recommendations. EDBT 2016: 712-713 - [c35]Omar Backhoff, Eirini Ntoutsi:
Scalable Online-Offline Stream Clustering in Apache Spark. ICDM Workshops 2016: 37-44 - [c34]Markus Mauder, Yulia Bobkova, Eirini Ntoutsi:
GMMbuilder - User-Driven Discovery of Clustering Structure for Bioarchaeology. ECML/PKDD (3) 2016: 8-11 - [c33]Eirini Ntoutsi, Kostas Stefanidis:
Recommendations beyond the ratings matrix. DDI@WebSci 2016: 2:1-2:5 - 2015
- [j8]Max Zimmermann, Eirini Ntoutsi, Myra Spiliopoulou:
Discovering and monitoring product features and the opinions on them with OPINSTREAM. Neurocomputing 150: 318-330 (2015) - [c32]Vasilis Efthymiou, Kostas Stefanidis, Eirini Ntoutsi:
Top-k computations in MapReduce: A case study on recommendations. IEEE BigData 2015: 2820-2822 - [c31]Sebastian Wagner, Max Zimmermann, Eirini Ntoutsi, Myra Spiliopoulou:
Ageing-Based Multinomial Naive Bayes Classifiers Over Opinionated Data Streams. ECML/PKDD (1) 2015: 401-416 - [c30]Michael Stockerl, Christoph Ringlstetter, Matthias Schubert, Eirini Ntoutsi, Hans-Peter Kriegel:
Online template matching over a stream of digitized documents. SSDBM 2015: 9:1-9:12 - [c29]Markus Mauder, Eirini Ntoutsi, Peer Kröger, Gisela Grupe:
Data mining for isotopic mapping of bioarchaeological finds in a central european alpine passage. SSDBM 2015: 34:1-34:6 - [i1]Max Zimmermann, Eirini Ntoutsi, Myra Spiliopoulou:
Incremental Active Opinion Learning Over a Stream of Opinionated Documents. CoRR abs/1509.01288 (2015) - 2014
- [c28]Eirini Ntoutsi, Kostas Stefanidis, Katharina Rausch, Hans-Peter Kriegel:
"Strength Lies in Differences": Diversifying Friends for Recommendations through Subspace Clustering. CIKM 2014: 729-738 - [c27]Max Zimmermann, Eirini Ntoutsi, Myra Spiliopoulou:
A Semi-Supervised Self-Adaptive Classifier over Opinionated Streams. ICDM Workshops 2014: 425-432 - [c26]Max Zimmermann, Eirini Ntoutsi, Myra Spiliopoulou:
Adaptive semi supervised opinion classifier with forgetting mechanism. SAC 2014: 805-812 - [c25]Katharina Rausch, Eirini Ntoutsi, Kostas Stefanidis, Hans-Peter Kriegel:
Exploring subspace clustering for recommendations. SSDBM 2014: 42:1-42:4 - 2013
- [j7]Hans-Peter Kriegel, Eirini Ntoutsi:
Clustering high dimensional data: examining differences and commonalities between subspace clustering and text clustering - a position paper. SIGKDD Explor. 15(2): 1-8 (2013) - [j6]Kostas Stefanidis, Eirini Ntoutsi, Mihalis Petropoulos, Kjetil Nørvåg, Hans-Peter Kriegel:
A Framework for Modeling, Computing and Presenting Time-Aware Recommendations. Trans. Large Scale Data Knowl. Centered Syst. 10: 146-172 (2013) - [c24]Max Zimmermann, Eirini Ntoutsi, Myra Spiliopoulou:
Extracting Opinionated (Sub)Features from a Stream of Product Reviews. Discovery Science 2013: 340-355 - [c23]Myra Spiliopoulou, Eirini Ntoutsi, Yannis Theodoridis, René Schult:
MONIC and Followups on Modeling and Monitoring Cluster Transitions. ECML/PKDD (3) 2013: 622-626 - 2012
- [j5]Eirini Ntoutsi, Myra Spiliopoulou, Yannis Theodoridis:
FINGERPRINT: Summarizing Cluster Evolution in Dynamic Environments. Int. J. Data Warehous. Min. 8(3): 27-44 (2012) - [c22]Claudia Lauschke, Eirini Ntoutsi:
Monitoring User Evolution in Twitter. ASONAM 2012: 972-977 - [c21]Irene Ntoutsi, Kostas Stefanidis, Kjetil Nørvåg, Hans-Peter Kriegel:
gRecs: A Group Recommendation System Based on User Clustering. DASFAA (2) 2012: 299-303 - [c20]Kostas Stefanidis, Irene Ntoutsi, Kjetil Nørvåg, Hans-Peter Kriegel:
A Framework for Time-Aware Recommendations. DEXA (2) 2012: 329-344 - [c19]Eirini Ntoutsi, Kostas Stefanidis, Kjetil Nørvåg, Hans-Peter Kriegel:
Fast Group Recommendations by Applying User Clustering. ER 2012: 126-140 - [c18]Max Zimmermann, Irene Ntoutsi, Zaigham Faraz Siddiqui, Myra Spiliopoulou, Hans-Peter Kriegel:
Discovering global and local bursts in a stream of news. SAC 2012: 807-812 - [c17]Irene Ntoutsi, Arthur Zimek, Themis Palpanas, Peer Kröger, Hans-Peter Kriegel:
Density-based Projected Clustering over High Dimensional Data Streams. SDM 2012: 987-998 - 2011
- [c16]Irene Ntoutsi, Myra Spiliopoulou, Yannis Theodoridis:
Summarizing Cluster Evolution in Dynamic Environments. ICCSA (2) 2011: 562-577 - [c15]Nikos Mitsou, Irene Ntoutsi, Dirk Wollherr, Costas S. Tzafestas, Hans-Peter Kriegel:
Revealing Cluster Formation over Huge Volatile Robotic Data. ICDM Workshops 2011: 450-457 - [c14]Hans-Peter Kriegel, Peer Kröger, Irene Ntoutsi, Arthur Zimek:
Density Based Subspace Clustering over Dynamic Data. SSDBM 2011: 387-404 - 2010
- [c13]Hans-Peter Kriegel, Peer Kröger, Irene Ntoutsi, Arthur Zimek:
Towards subspace clustering on dynamic data: an incremental version of PreDeCon. StreamKDD@KDD 2010: 31-38
2000 – 2009
- 2009
- [j4]Irene Ntoutsi, Myra Spiliopoulou, Yannis Theodoridis:
Tracing cluster transitions for different cluster types. Control. Cybern. 38(1): 239-259 (2009) - [j3]Ilaria Bartolini, Paolo Ciaccia, Irene Ntoutsi, Marco Patella, Yannis Theodoridis:
The Panda framework for Comparing Patterns. Data Knowl. Eng. 68(2): 244-260 (2009) - 2008
- [b1]Eirini Ntoutsi:
Ζητήματα ομοιότητας στην εξόρυξη γνώσης: Μεθοδολογίες και τεχνικές. University of Piraeus, Greece, 2008 - [j2]Irene Ntoutsi, Nikos Mitsou, Gerasimos Marketos:
Traffic mining in a road-network: How does the traffic flow? Int. J. Bus. Intell. Data Min. 3(1): 82-98 (2008) - [c12]Evangelos E. Kotsifakos, Irene Ntoutsi, Yannis Vrahoritis, Yannis Theodoridis:
Pattern-Miner: integrated management and mining over data mining models. KDD 2008: 1081-1084 - [c11]Gerasimos Marketos, Elias Frentzos, Irene Ntoutsi, Nikos Pelekis, Alessandra Raffaetà, Yannis Theodoridis:
Building real-world trajectory warehouses. MobiDE 2008: 8-15 - [c10]Evangelos E. Kotsifakos, Irene Ntoutsi, Yannis Vrahoritis, Yannis Theodoridis:
Monitoring Patterns through an Integrated Management and Mining Tool. ECML/PKDD (2) 2008: 678-683 - [c9]Irene Ntoutsi, Alexandros Kalousis, Yannis Theodoridis:
A general framework for estimating similarity of datasets and decision trees: exploring semantic similarity of decision trees. SDM 2008: 810-821 - [c8]Irene Ntoutsi, Yannis Theodoridis:
Comparing Datasets Using Frequent Itemsets: Dependency on the Mining Parameters. SETN 2008: 212-225 - [p3]José Antônio Fernandes de Macêdo, Christelle Vangenot, Walied Othman, Nikos Pelekis, Elias Frentzos, Bart Kuijpers, Irene Ntoutsi, Stefano Spaccapietra, Yannis Theodoridis:
Trajectory Data Models. Mobility, Data Mining and Privacy 2008: 123-150 - [p2]Elias Frentzos, Nikos Pelekis, Irene Ntoutsi, Yannis Theodoridis:
Trajectory Database Systems. Mobility, Data Mining and Privacy 2008: 151-187 - [p1]Nikos Pelekis, Alessandra Raffaetà, Maria Luisa Damiani, Christelle Vangenot, Gerasimos Marketos, Elias Frentzos, Irene Ntoutsi, Yannis Theodoridis:
Towards Trajectory Data Warehouses. Mobility, Data Mining and Privacy 2008: 189-211 - 2007
- [c7]Nikos Pelekis, Ioannis Kopanakis, Irene Ntoutsi, Gerasimos Marketos, Yannis Theodoridis:
Mining Trajectory Databases via a Suite of Distance Operators. ICDE Workshops 2007: 575-584 - [c6]Nikos Pelekis, Ioannis Kopanakis, Gerasimos Marketos, Irene Ntoutsi, Gennady L. Andrienko, Yannis Theodoridis:
Similarity Search in Trajectory Databases. TIME 2007: 129-140 - 2006
- [c5]Myra Spiliopoulou, Irene Ntoutsi, Yannis Theodoridis, René Schult:
MONIC: modeling and monitoring cluster transitions. KDD 2006: 706-711 - 2005
- [c4]Evangelos E. Kotsifakos, Irene Ntoutsi, Yannis Theodoridis:
Database Support for Data Mining Patterns. Panhellenic Conference on Informatics 2005: 14-24 - 2004
- [c3]Irene Ntoutsi:
The Notion of Similarity in Data and Pattern Spaces. PaRMa 2004 - [c2]Ilaria Bartolini, Paolo Ciaccia, Irene Ntoutsi, Marco Patella, Yannis Theodoridis:
A Unified and Flexible Framework for Comparing Simple and Complex Patterns. PKDD 2004: 496-499 - 2002
- [c1]Dimitrios Kalles, Eirini Ntoutsi:
Interactive Verification of Game Design and Playing Strategies. ICTAI 2002: 425-430 - 2000
- [j1]Dimitrios Kalles, Athanassios Papagelis, Eirini Ntoutsi:
Induction of decision trees in numeric domains using set-valued attributes. Intell. Data Anal. 4(3-4): 323-347 (2000)
Coauthor Index
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