Intelligent Systems Lab

E. Kouloumpris, K. Moutsianas, and I. Vlahavas. “SABER: Stochastic-Aware Bootstrap Ensemble Ranking for portfolio management”. Expert Systems with Applications, Vol. 249, Part B, no. 1, p. 123637. issn: 0957-4174., 2024, DOI: https://doi.org/10.1016/j.eswa.2024.123637

Vasileios Kochliaridis, Anastasia Papadopoulou, Ioannis Vlahavas, "UNSURE - A Machine Learning Approach to Cryptocurrency Trading", Accepted in Applied Intelligence, Springer, 2024

E. Kouloumpris, A. Lazaridis, A. Fachantidis, and I. Vlahavas. “Diagnosing Attention Deficit Hyperactivity Disorder Using Machine Learning Methods on Serious Game-generated Data”. International Journal on Artificial Intelligence Tools, Vol. 33, no. 1, p. 2350059. issn: 1793-6349., 2024, DOI: https://doi.org/10.1142/S0218213023500598

Dimitriadis, D., Tsoumakas, G. (2023) Enhancing Yes/No Question Answering with Weak Supervision via Extractive Question Answering, Applied Intelligence 53(22)

Gidiotis, A., Tsoumakas, G. (2023) Bayesian Active Summarization. Computer Speech & Language, Vol. 83, pages 101553

Avramelou, L., Passalis, N., Tsoumakas, G., Tefas, A. (2023) Domain-Specific Large Language Model Finetuning using a Model Assistant for Financial Text Summarization, Proc. 2023 IEEE Symposium Series on Computational Intelligence (SSCI 2023), Mexico City, Mexico.

C. Gkoutroumpi, N. Virtsionis Gkalinikis, D. Vrakas. SGAN: Appliance signatures data generation for NILM applications using GANs, To be presented in the 12th Computing Conference 2024, London UK, (2024)

Lentzas, Athanasios & Vrakas, Dimitris. (2023). From Robot Self-Localization to Global-Localization: An RSSI Based Approach.. Electronic Proceedings in Theoretical Computer Science. 391. 18-25. 10.4204/EPTCS.391.4.

Kamtziridis, G., Vrakas, D. & Tsoumakas, G. Does noise affect housing prices? A case study in the urban area of Thessaloniki. EPJ Data Sci. 12, 50 (2023). https://doi.org/10.1140/epjds/s13688-023-00424-3

Dimitrios Zaikis, Stefanos D. Stefanidis, Konstantinos Anagnostopoulos, and Ioannis Vlahavas. “Aristoxenus at SemEval-2023 Task 4: A Domain-Adapted Ensemble Approach to the Identification of Human Values behind Arguments.” In: Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023). Toronto, Canada: Association for Computational Linguistics, 2023, pp. 1037–1043. doi: 10.18653/v1/2023.semeval-1.142. url: https://aclanthology.org/2023.semeval-1.142

Dimitrios Zaikis, Stylianos Kokkas, and Ioannis Vlahavas. “DACL: A Domain-Adapted Contrastive Learning Approach to Low Resource Language Representations for Document Clustering Tasks.” In: Engineering Applications of Neural Networks. Ed. by Lazaros Iliadis, Ilias Maglogiannis, Serafin Alonso, Chrisina Jayne, and Elias Pimenidis. Vol. 1826. Series Title: Communications in Computer and Information Science. Cham: Springer Nature Switzerland, 2023, pp. 585–598. isbn: 978-3-031-34203-5 978-3-031-34204-2. doi: 10.1007/978-3-031-34204-2_47. url: https://link.springer.com/10.1007/978-3-031-34204-2_47.

Georgios Aivatoglou, Alexia Fytili, Georgios Arampatzis, Dimitrios Zaikis, Stylianou Nikolaos, and Ioannis Vlahavas. “End-to-end Aspect Extraction and Aspect-Based Sentiment Analysis Framework for Low-Resource Languages.” In: Intelligent Systems Conference (IntelliSys) 2023. Series Title: Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2023.

Dimitrios Zaikis and Ioannis Vlahavas. “From Pre-Training to Meta-Learning: A Journey in Low-Resource-Language Representation Learning.” In: IEEE Access 11 (Oct. 2023). IF: 3.9, pp. 115951–115967. doi: 10.1109/ACCESS.2023.3326337. url: https://ieeexplore.ieee.org/document/10288436.

Dimitrios Zaikis, Nikolaos Stylianou, and Ioannis Vlahavas. “PIMA: Parameter-Shared Intelligent Media Analytics Framework for Low Resource Languages.” In: Applied Sciences 13.5 (Mar. 2023). IF: 2.7, p. 3265. issn: 2076-3417. doi: 10.3390/app13053265. url: https://www.mdpi.com/2076-3417/13/5/3265.

B. Liu, J. Wang, K. Sun, G. Tsoumakas (2023), Fine-grained selective similarity integration for drug–target interaction prediction, Briefings in Bioinformatics

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.