Expertises
Mathematics
- Imputation Method
- Missing Value
- Handling Missing Data
- Performance Model
- Regression Model
Computer Science
- Meta-Learning
- Data Mechanism
- Large Language Model
Organisaties
Publicaties
2026
Handling missing data with meta-learning and large language models (2026)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Baysal Erez, I.https://doi.org/10.3990/1.9789036570633Sparse GAIN: Imputation Methods to Handle Missing Values with Sparse Initialization (2026)In Intelligent Data Engineering and Automated Learning – IDEAL 2025: 26th International Conference, Jaén, Spain, November 13–15, 2025, Proceedings, Part I (pp. 232-238) (Lecture Notes in Computer Science; Vol. 16238). Springer. van Oers, B. P., Baysal Erez, I. & van Keulen, M.https://doi.org/10.1007/978-3-032-10486-1_22
2025
Extended MetaLIRS: Meta-learning for Imputation and Regression Selection Model with Explainability for Different Missing Data Mechanisms (2025)International Journal of Data Science and Analytics, 20(6), 5895-5920. Article 102587. Baysal Erez, I., Flokstra, J., Poel, M. & van Keulen, M.https://doi.org/10.1007/s41060-025-00808-w
2024
MetaLIRS: Meta-learning for Imputation and Regression Selection (2024)In Intelligent Data Engineering and Automated Learning - IDEAL 2024: 25th International Conference, Valencia, Spain, November 20-22, 2024. Proceedings, Part I (pp. 155-166) (Lecture Notes in Computer Science; Vol. 15346). Springer. Baysal Erez, I., Flokstra, J., Poel, M. & van Keulen, M.https://doi.org/10.1007/978-3-031-77731-8_15The interaction between imputation and regression models (2024)[Contribution to conference › Poster] 22nd International Conference of AI in Medicine, AIME 2024. Baysal Erez, I., Flokstra, J., Poel, M. & van Keulen, M.The Impact of Missing Data Imputation on Model Performance and Explainability (2024)[Contribution to conference › Paper] BNAIC/BeNeLearn 2024. Baysal Erez, I., Flokstra, J., Poel, M. & van Keulen, M.
2023
Investigating Imputation Methods for Handling Missing Data (2023)[Contribution to conference › Poster] Joint International Scientific Conferences on AI and Machine Learning, BNAIC/BeNeLearn 2023. Maas, J., Römer, J. G. W. T., Baysal Erez, I. & van Keulen, M.Investigating Imputation Methods for Handling Missing Data (2023)[Contribution to conference › Paper] Joint International Scientific Conferences on AI and Machine Learning, BNAIC/BeNeLearn 2023. Maas, J., Römer, J. G. W. T., Baysal Erez, I. & van Keulen, M.
2022
Understanding dynamic sparse training capabilities in accommodating sparse data (2022)[Contribution to conference › Paper] European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2022. Baysal Erez, I. & van Keulen, M.The mutually reinforcing of sparse data and sparse training models (2022)[Contribution to conference › Poster] SIAM International Conference on Data Mining, SDM 2022. Baysal Erez, I.
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