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Baydogan, M. Gokce, G. Runger, and E. Tuv, "A Bag-of-Features Framework to Classify Time Series", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, pp. 2796-2802, 2013.
Adıyeke, E., and M. Gokce Baydogan, "The benefits of target relations: A comparison of multitask extensions and classifier chains", Pattern Recognition, vol. 107, pp. 107507, 2020.
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Baydogan, M. Gokce, and G. Runger, "Learning a symbolic representation for multivariate time series classification", Data Mining and Knowledge Discovery, vol. 29, issue 2: Springer US, pp. 400-422, 03/2015.
Sivrikaya, Ö. Emre, M. Yükselgönül, and M. Gokce Baydogan, "Learning prototypes for multiple instance learning.", Turkish Journal of Electrical Engineering & Computer Sciences, vol. 29, 2021.
Küçükaşcı, E. Şeyma, M. Gokce Baydogan, and Z. C. Taşkın, "A linear programming approach to multiple instance learning", Turkish Journal of Electrical Engineering & Computer Sciences, vol. 29, pp. 2186–2201, 2021.
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Altay, T., and M. Gokce Baydogan, "A scale-space theory and bag-of-features based time series classification method", Signal Processing and Communications Applications Conference (SIU), 2017 25th: IEEE, 2017.
Adıyeke, E., and M. Gokce Baydogan, "Semi-supervised extensions of multi-task tree ensembles", Pattern Recognition, vol. 123, pp. 108393, 2022.
Deng, H., M. Gokce Baydogan, and G. Runger, "SMT: Sparse multivariate tree", Statistical Analysis and Data Mining, vol. 7, issue 1, pp. 53-69, 02/2014.