Refereed Journal Papers

  1. Erhan Can Özcan, Berk Görgülü and Mustafa Gökçe Baydoğan, “Column Generation-based Prototype Learning for Optimizing Area Under the Receiver Operating Characteristic Curve”, European Journal of Operational Research, accepted for publication, 2023. (link)   (supporting page and codes) 
  2. Hadi Jahanshahi and Mustafa Gokce Baydogan, “nTreeClus: a Tree-based Sequence Encoder for Clustering Categorical Series”, Neurocomputing, vol 494, pp.224-241, 2022. (link)  (supporting page and codes)
  3. Esra Adıyeke and Mustafa Gokce Baydogan, “Semi-supervised extensions of multi-task tree ensembles”, Pattern Recognition, vol. 123, 2022. (link)(codes)
  4. Emel Şeyma Küçükaşcı, Mustafa Gokce Baydogan, Z. Caner Taşkın, “Multiple Instance Classification via Quadratic Programming”, Journal of Global Optimization, 2022. (link) (supporting page and codes)
  5. Igor Ilic, Berk Görgülü, Mucahit Cevik and Mustafa Gokce Baydogan, “Explainable boosted linear regression for time series forecasting”, Pattern Recognition,  vol.120, 2021. (link) (codes)
  6. Berk Görgülü and Mustafa Gokce Baydogan, “Randomized Trees for Time Series Representation and Similarity”, Pattern Recognition,  vol.120,  2021. (link) (codes)
  7. Esra Adıyeke and Mustafa Gokce Baydogan, “An ensemble-based semi-supervised feature ranking for multi-target regression problems”, Pattern Recognition Letters,  vol.248, pp. 36-42, 2021. (link) (codes)
  8. Tayip Altay and Mustafa Gokce Baydogan, “A new feature-based time series classification method by using scale-space extrema”, Engineering Science and Technology, an International Journal,  vol.24, no.6, pp.1490-1497, 2021. (link)
  9. Özgür Emre Sivrikaya, Mert Yüksekgönül and Mustafa Gokce Baydogan, “Learning Prototypes for Multiple Instance Learning”, Turkish Journal of Electrical Engineering and Computer Sciences, vol.29, no.7, pp.2901-2919, 2021. (link) (supporting page and codes)
  10. Emel Şeyma Küçükaşcı, Mustafa Gokce Baydogan, Z. Caner Taşkın, “A Linear Programming Approach to Multiple Instance Learning”, Turkish Journal of Electrical Engineering and Computer Sciences,  vol.29, no.4, pp.2186-2201, 2021. (link) (supporting page and codes)
  11. Esra Adiyeke and Mustafa Gokce Baydogan, “The benefits of target relations: A comparison of multitask extensions and classifier chains”, Pattern Recognition,  vol.107, 2020. (link)
  12. Ilgin Gokasar, Yigit Cetinel and Mustafa Gokce Baydogan, “Estimation of Influence Distance of Bus Stops Using Bus GPS Data and Bus Stop Properties”, IEEE Transactions on Intelligent Transportation Systems,  vol.20, no.12, pp. 4635-4642, 2019. (link)
  13. Mert Edali, Mustafa Gokce Baydogan and Gonenc Yucel, “Classification of generic system dynamics model outputs via supervised time series pattern discovery”, Turkish Journal of Electrical Engineering and Computer Sciences,  vol. 27, no.2,  pp. 832-846, 2019. (link)
  14. Hande Cakin, Berk Gorgulu, Mustafa Gokce Baydogan, Na Zou and Jing Li, “A Data Adaptive Biological Sequence Representation for Supervised Learning”, Journal of Healthcare Informatics Research,  vol. 2, no.4,  pp. 448-471, 2018. (link) 
  15. Emel Şeyma Küçükaşcı and Mustafa Gokce Baydogan, “Encoding Strategies for Bag Representation in Multiple Instance Learning Problems”, Information Sciences,  vol. 467, pp. 559-578, 2018. (link) (supporting page and codes)
  16. Kerem Tuncel and Mustafa Gokce Baydogan, “Autoregressive Forests for Multivariate Time Series Modeling”, Pattern Recognition, vol. 73, pp. 202-215, 2018. (link) (supporting page and codes)
  17. Mustafa Gokce Baydogan and George Runger, “Time series representation and similarity based on local autopatterns”, Data Mining and Knowledge Discovery, vol. 30, no.2, pp.476-509, 2016.  (link) (supporting page) (codes) (mts datasets)
  18. Na Zou, Yun Zhu, Ji Zhu, Mustafa Gokce Baydogan, Wei Wang, Jing Li “A transfer learning approach for predictive modeling of degenerate biological systems.”, Technometrics, vol. 57, no. 3, pp.362-373, 2015 (link).
  19. Na Zou, Gael Chetelat, Mustafa Gokce Baydogan, Jing Li, Florian Fischer, Dmitry Titov, Juergen Dukart, Andreas Fellgiebel, Mathias Schreckenberger, Igor Yakushev, “Metabolic connectivity as index of verbal working memory”, Journal of Cerebral Blood Flow and Metabolism, vol.35, no.7, pp.1122-1126, Mar. 2015. (link)
  20. Mustafa Gokce Baydogan and George Runger, “Learning a Symbolic Representation for Multivariate Time Series Classification”, Data Mining and Knowledge Discovery, vol.29, no.2, pp.400-422, Mar. 2015 (link) (supporting page) (codes) (mts datasets)
  21. Houtao Deng, Mustafa Gokce Baydogan, George Runger, “SMT: Sparse Multivariate Tree”, Statistical Analysis and Data Mining, vol.7, no.1, pp.53-69, Feb. 2014. (link) (supporting page) (codes are available on the supporting page)
  22. Mustafa Gokce Baydogan, George Runger, Eugene Tuv, “A Bag-of-Features Framework to Classify Time Series,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, no.11, pp.2796-2802, Nov. 2013 (link) (supporting page) (codes)
  23. Nong Ye, Stephen S. Yau, Dazhi Huang, Mustafa Baydogan,  Billibaldo M. Aranda, Auttawut Roontiva, Patrick Hurley, “Models of dynamic relations among service activities, system state and service quality on computer and network systems,”  Information, Knowledge, Systems Management, vol. 9, no.2, pp. 99-116, 2010 (link)
  24. Stephen S. Yau, Nong Ye, Hessam S. Sarjoughian, Dazhi Huang, Auttawut Roontiva, Mustafa Gokce Baydogan, Mohammed A. Muqsith, “Toward Development of Adaptive Service-Based Software Systems,” IEEE Transactions on Services Computing, vol. 2, no. 3, pp. 247-260, 2009. (link)

Book Chapters

  1. Javier Gonzalez-Sanchez, Mustafa Baydogan, Maria Elena Chavez-Echeagaray, Robert K. Atkinson and Winslow Burleson, Chapter 11 – Affect Measurement: A Roadmap Through Approaches, Technologies, and Data Analysis, In Emotions and Affect in Human Factors and Human-Computer Interaction, San Diego, 2017, Pages 255-288, 2017. (link)

Submitted  / Under Revision Papers

  1. Mustafa Gokce Baydogan and George Runger, “Supervised Time Series Pattern Discovery through Local Importance,” to Knowledge and Information Systems (submitted, October 8th, 2012, received major revision on September 22nd 2013 – submitted revisions on December 21st, 2013) (supporting page) (codes) – Received 2 major revisions over 3 years (long review times) and not considering submission for now.

Refereed Conference & Workshop Papers

  1. Altay, T. and Baydogan, M. G., 2017, “A scale-space theory and bag-of-features based time series classification method”, 25th IEEE Signal Processing and Communications Applications Conference (SIU).
  2. Balkan, S., Baydogan, M. G., Sanjay, A. V., 2015, “Adaptive Advertisement Recommender Systems for Digital Signage”, 2015 Americas Conference on Information Systems (AMCIS), accepted.
  3. Gonzalez-Sanchez, J., Chavez-Echeagaray, M. E., Lin, L., Baydogan, M., Christopherson, R., Gibson, D., and Atkinson, R. K., 2013. “Affect Recognition in Learning Scenarios: Matching BCI-based Values and Face-Based Values,” 13th IEEE International Conference on Advanced Learning Technologies, Beijing, China. (link)
  4. N. Ye, S. S. Yau, D. Huang, M. Baydogan, B. Aranda, A. Roontiva, and P. Hurley, “Cause-effect dynamics of computer and network systems for QoS,” The Proceedings of the 2010 Industrial Engineering Research Conference, 2010. (link)

Papers in Local Journals

  1. Baydoğan M.G.,  Akıllıoğlu H., Halıcı A., Canbaz D., Bolatlı Y., “Design of an Internal Milk Run Distribution System for a Diesel Injector Manufacturer”, Endüstri Mühendisliği Dergisi, 17 (3), 2-15, 2006. (link)