Refereed Journal and Proceedings Articles

  1. Bagirov A.M., Taheri S., Joki K., Karmitsa N., Makela M.M. (2024) Nonsmooth DC Optimization Support Vector Machines Method for Piecewise Linear Regression, Applied and Computational Mathematics
  2. Ersozlu, Z., Taheri S, Koch, I. (2024) A Review of Machine Learning Methods Used for Educational Data, Education and Information Technologies
  3. Martin J, Taheri S, Abdollahian M. (2024) Optimizing Ensemble Learning to Reduce Misclassification Costs in Credit Risk Scorecards. Mathematics, 12(6):855. https://doi.org/10.3390/math12060855
  4. Mousli, Sh., Taheri, S., He, J. (2024) Identifying Autism Spectrum Disorder Using Optimization-Based Clustering , International Journal of Computer and Information Engineering, 18 (2).
  5. Karmitsa N., Taheri S., Joki K., Paasivirta, P., Bagirov A.M., Makela M.M. (2023) Nonsmooth Optimization-based Hyperparameter-free Neural Networks for Large-scale Regression, Machine Learning Algorithms for Big Data Analysis, Algorithms, 16(9), 444; https://doi.org/10.3390/a16090444
  6. Gaudioso M., Taheri S., Bagirov A.M., Karmitsa N. (2023) Bundle Enrichment Method for Nonsmooth DC Programming, Numerical Optimization in Honor of the 60th Birthday of Marko M. Mäkelä, Algorithms, 16(8), 394; https://doi.org/10.3390/a16080394
  7. Lee KH, Abdollahian M, Schreider S, Taheri S. (2023) Supply Chain Demand Forecasting and Price Optimisation Models with Substitution Effect, Advances of Machine Learning and Data Mining Using Mathematical Optimization in Honor of the 65th Birthday of Prof. Adil M. Bagirov, Mathematics, 11(11):2502; https://doi.org/10.3390/math11112502
  8. Bagirov A.M., Hoseini Monjezi N., Taheri S., (2023) A Novel Optimization Approach Towards Improving Separability of Clusters, Computers & Operations Research, DOI: 10.1016/j.cor.2022.106135
  9. Qiang Long, Bagirov A.M., Taheri S., Sultanova N., Xue Wu., (2023) Methods and Applications of Clusterwise Linear Regression: A survey and comparison, ACM Transactions on Knowledge Discovery from Data, DOI: 10.1145/3550074
  10. Bagirov A.M., Taheri S., Ordin, B., (2022) An Adaptive k-Medians Clustering Algorithm, Problems of Information Technology (2022), 13(2), 3–15, DOI: 0.25045/jpit.v13.i2.01
  11. Insania N., Akman D., Taheri S., Hearne J., (2022) Short-Notice Flood Evacuation Plan Under Dynamic Demand in High Populated Areas, International Journal of Disaster Risk Reduction.
  12. Bagirov A.M., Taheri S., Karmitsa N., Sultanova N., Asadi, S., (2022) Robust Piecewise Linear L1-Regression via Nonsmooth DC Optimization, Optimization Methods and Software, DOI: 10.1080/10556788.2020.1855171
  13. Bagirov A.M., Taheri S., Bai F., Zheng F., (2021) Nonsmooth Optimization based Model and Algorithm for Semi-Supervised Clustering, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2021.3129370.
  14. Bagirov A.M., Hoseini Monjezi N., Taheri S., (2021) An augmented subgradient method for minimizing nonsmooth DC functions, Computational Optimization and Applications, DOI: https://doi.org/10.1007/s10589-021-00304-4.
  15. Bagirov A.M., Taheri S., Cimen, E. (2021) Incremental DC Optimization Algorithm for Large-Scale Clusterwise Linear Regression, Journal of Computational and Applied Mathematics, 389.
  16. Bagirov A.M., Taheri S., Joki K., Karmitsa N., Makela M.M. (2021) Aggregate Subgradient Method for Nonsmooth DC Optimization, Optimization Letters, https://doi.org/10.1007/s11590-020-01586-z
  17. Joki K., Bagirov A.M., Karmitsa N., Makela M.M., Taheri S., (2020) Clusterwise Support Vector Linear Regression, European Journal of Operational Research, 287(1), 19–35.
  18. Karmitsa N., Taheri S., Bagirov A.M., Makinen, P., (2020) Missing Value Imputation via Clusterwise Linear Regression, IEEE Transactions on Knowledge and Data Engineering
  19. Taheri S., Bagirov A.M., Gondal, I., Brown, S. (2020) Cyber-Attack Triage using Incremental Clustering for Intrusion Detection Systems, International Journal of Information Security, 19, 597–607.
  20. Bagirov A.M., Taheri S., Asadi, S. (2019) A Difference of Convex Optimization Algorithm for Piecewise Linear Regression, Journal of Industrial and Management Optimization (JIMO), 15(2), 909–932
  21. Karmitsa N., Bagirov A.M., Taheri S. (2018) Clustering in Large Data sets with the Limited Memory Bundle Method, Pattern Recognition, 83, 245–259
  22. Joki K., Bagirov A.M., Karmitsa N., Makela M.M., Taheri S. (2018) Double Bundle Method for Finding Clarke Stationary Points in Nonsmooth DC-Programming, SIAM Journal on Optimization, 28(2), 1892–1919
  23. Karmitsa N., Bagirov A.M., Taheri S. (2017) New Diagonal Bundle Method for Clustering Problems in Large Data Sets, European Journal of Operational Research (EJOR), 263 (2), 367–379
  24. Bagirov A.M., Taheri S. (2017) An Algorithm based on Optimization for Clustering Data using an L1-norm, International Journal of Operations Research (IJOR), 8(2), 2–24
  25. Bagirov A.M., Taheri S. (2017) DC Programming Algorithm for Clusterwise Linear L1- Regression, Journal of the Operations Research Society of China (JORC), 5(2), 233–256
  26. Bagirov A.M., Taheri S., Ugon, J. (2016) Nonsmooth DC Programming Approach to the Minimum Sum-of-Squares Clustering Problems, Pattern Recognition, 53, 12–24
  27. Taheri S., Mammadov M. (2015) Structure Learning of Bayesian Networks using Global Optimization with Applications in Data Classification, Optimization Letters, 9(5), 931–948
  28. Taheri S., Mammadov M., Seifollahi S. (2015) Globally Convergent Algorithms for Solving Unconstrained Optimization Problems, Optimization, 64(2), 249-263
  29. Taheri S., Yearwood J., Mammadov M., Seifollahi S. (2014) Attribute Weighted Naive Bayes Classifier Using a Local Optimization, Neural Computing and Applications, 24(5), 995–1002
  30. Taheri S., Mammadov M. (2013) Learning Naive Bayes Classifier with Optimization Models, International Journal of Applied Mathematics and Computer Science, 23(4), 787–795
  31. Taheri S., Mammadov M. (2012) Solving Systems of Nonlinear Equations using a Globally Convergent Optimization Algorithm, Global Journal of Technology and Optimization, 3, 132–138
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