Mollas

N. Mylonas, I. Mollas, N. Bassiliades, G. Tsoumakas, “Exploring Local Interpretability in Dimensionality Reduction: Analysis and Use Cases”, Expert Systems with Applications, Volume 252, Part A, 124074, 2024.
Katsaki, S., Aivazidis, C., Mylonas, N., Mollas, I., Tsoumakas, G. (2023) On the Adaptability of Attention-Based Interpretability in Different Transformer Architectures for Multi-Class Classification Tasks, Proceedings of the AIMLAI Workshop of ECML PKDD 2023.
Bardos, A., Mylonas, N., Mollas, I., Tsoumakas, G. (2023) Local interpretability of random forests for multi-target regression, Proceedings of the AIMLAI Workshop of ECML PKDD 2023.
Mylonas, N., Mollas, I. & Tsoumakas, G. An attention matrix for every decision: faithfulness-based arbitration among multiple attention-based interpretations of transformers in text classification. Data Min Knowl Disc (2023). https://doi.org/10.1007/s10618-023-00962-4
D. Akrivousis, N. Mylonas, I. Mollas and G. Tsoumakas, "Text classification is keyphrase explainable! Exploring local interpretability of transformer models with keyphrase extraction," 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), Thessaloniki, Greece, 2023, pp. 1-9, doi: 10.1109/DSAA60987.2023.10302566.
N. Mylonas, I. Mollas, B. Liu, Y. Manolopoulos and G. Tsoumakas, "On the Persistence of Multilabel Learning, Its Recent Trends, and Its Open Issues," in IEEE Intelligent Systems, vol. 38, no. 2, pp. 28-31, March-April 2023, doi: 10.1109/MIS.2023.3255591.
N. Mylonas, I. Mollas and G. Tsoumakas, "Beyond Annual Revisions: A Multi-Label Concept Drift Analysis of MeSH", 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS), L'Aquila, Italy, 2023, pp. 157-162, doi: 10.1109/CBMS58004.2023.00209.
I. Mollas, N. Bassiliades, G. Tsoumakas, "Truthful meta-explanations for local interpretability of machine learning models", Applied Intelligence, 53, pp. 26927–26948, 2023.
N. Mylonas, I. Mollas, N. Bassiliades, G. Tsoumakas, “Local Multi-Label Explanations for Random Forest”, 4th International Workshop on eXplainable Knowledge Discovery in Data Mining (XKDD 2022), 19 Sep 2022, Grenoble, France, In I. Koprinska et al. (Eds.): ECML PKDD 2022 Workshops, CCIS 1752, pp. 369–384, Springer Nature, 2023.
A. Bardos, I. Mollas, N. Bassiliades, G. Tsoumakas, "Local Explanation of Dimensionality Reduction", 12th Hellenic Conference on Artificial Intelligence (SETN 2022), Sep 7-9, 2022, Corfu, Greece. ACM, New York, NY, USA, Article 29, 1–9.
Address

School of Informatics
Aristotle University of Thessaloniki
54124 Thessaloniki, Greece

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Prof. Ioannis P. Vlahavas
tel: ++30 231099-8145
fax: ++30 231099-8362
e-mail: vlahavas@csd.auth.gr

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