Petros Xanthopoulos, Ph.D.
Affiliations: | 2011 | University of Florida, Gainesville, Gainesville, FL, United States |
Area:
Industrial Engineering, Computer Science, Applied MathematicsGoogle:
"Petros Xanthopoulos"Parents
Sign in to add mentor| Panos M. Pardalos | grad student | 2011 | UF Gainesville (Computer Science Tree) | |
| (Robust data mining techniques with application in biomedicine and engineering.) | ||||
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Publications
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| Razmjoo A, Xanthopoulos P, Zheng QP. (2019) Feature importance ranking for classification in mixed online environments Annals of Operations Research. 276: 315-330 |
| Ünlü R, Xanthopoulos P. (2019) A weighted framework for unsupervised ensemble learning based on internal quality measures Annals of Operations Research. 276: 229-247 |
| Panagopoulos OP, Xanthopoulos P, Razzaghi T, et al. (2018) Relaxed support vector regression Annals of Operations Research. 276: 191-210 |
| Razmjoo A, Xanthopoulos P, Zheng QP. (2017) Online feature importance ranking based on sensitivity analysis Expert Systems With Applications. 85: 397-406 |
| Panagopoulos OP, Pappu V, Xanthopoulos P, et al. (2016) Constrained subspace classifier for high dimensional datasets Omega-International Journal of Management Science. 59: 40-46 |
| Rivera WA, Xanthopoulos P. (2016) A priori synthetic over-sampling methods for increasing classification sensitivity in imbalanced data sets Expert Systems With Applications. 66: 124-135 |
| Pappu V, Panagopoulos OP, Xanthopoulos P, et al. (2015) Sparse Proximal Support Vector Machines for feature selection in high dimensional datasets Expert Systems With Applications. 42: 9183-9191 |
| Haghtalab S, Xanthopoulos P, Madani K. (2015) A robust unsupervised consensus control chart pattern recognition framework Expert Systems With Applications. 42: 6767-6776 |
| Razzaghi T, Xanthopoulos P, Şeref O. (2015) Constraint relaxation, cost-sensitive learning and bagging for imbalanced classification problems with outliers Optimization Letters. 11: 915-928 |
| Xanthopoulos P, Razzaghi T. (2014) A weighted support vector machine method for control chart pattern recognition Computers & Industrial Engineering. 70: 134-149 |