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I. Baysal Erez (Işıl)

Guest PhD Candidate

Expertise

Engineering & Materials Science
Costs
Data Science
Data Storage Equipment
Deep Learning
Learning Algorithms
Neural Networks

Publications

Recent
Maas, J., Römer, J. G. W. T. , Baysal Erez, I. , & van Keulen, M. (2023). Investigating Imputation Methods for Handling Missing Data. Poster session presented at Joint International Scientific Conferences on AI and Machine Learning, BNAIC/BeNeLearn 2023, Delft, Netherlands.
Maas, J., Römer, J. G. W. T. , Baysal Erez, I. , & van Keulen, M. (2023). Investigating Imputation Methods for Handling Missing Data. Paper presented at Joint International Scientific Conferences on AI and Machine Learning, BNAIC/BeNeLearn 2023, Delft, Netherlands.
Baysal Erez, I. , & van Keulen, M. (2022). Understanding dynamic sparse training capabilities in accommodating sparse data. 1-6. Paper presented at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2022, Grenoble, France.
Baysal Erez, I. (2022). The mutually reinforcing of sparse data and sparse training models. Poster session presented at SIAM International Conference on Data Mining, SDM 2022.

UT Research Information System

Contact Details

Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11)
Hallenweg 19
7522NH  Enschede
The Netherlands

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Mailing Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
P.O. Box 217
7500 AE Enschede
The Netherlands