| Learning and soft computing: support vector machines, neural networks, and fuzzy logic models V Kecman MIT press, 2001 | 2956 | 2001 |
| Support vector machines–an introduction V Kecman Support vector machines: theory and applications, 1-47, 2005 | 550 | 2005 |
| Kernel based algorithms for mining huge data sets TM Huang, V Kecman, I Kopriva Springer, 2006 | 369 | 2006 |
| New approach to dynamic modelling of vapour-compression liquid chillers: artificial neural networks H Bechtler, MW Browne, PK Bansal, V Kecman Applied Thermal Engineering 21 (9), 941-953, 2001 | 265 | 2001 |
| Multiple regression and neural networks analyses in composites machining JT Lin, D Bhattacharyya, V Kecman Composites Science and Technology 63 (3-4), 539-548, 2003 | 161 | 2003 |
| Iterative single data algorithm for training kernel machines from huge data sets: Theory and performance V Kecman, TM Huang, M Vogt Support vector machines: Theory and Applications, 255-274, 2005 | 157 | 2005 |
| Multi-target support vector regression via correlation regressor chains G Melki, A Cano, V Kecman, S Ventura Information Sciences 415, 53-69, 2017 | 151 | 2017 |
| Combining support vector machine learning with the discrete cosine transform in image compression J Robinson, V Kecman IEEE Transactions on Neural Networks 14 (4), 950-958, 2003 | 136 | 2003 |
| Modelling of vapour-compression liquid chillers with neural networks DJ Swider, MW Browne, PK Bansal, V Kecman Applied thermal engineering 21 (3), 311-329, 2001 | 126 | 2001 |
| Gene extraction for cancer diagnosis by support vector machines—an improvement TM Huang, V Kecman Artificial Intelligence in Medicine 35 (1-2), 185-194, 2005 | 107 | 2005 |
| Neural networks—a new approach to model vapour‐compression heat pumps H Bechtler, MW Browne, PK Bansal, V Kecman International Journal of Energy Research 25 (7), 591-599, 2001 | 96 | 2001 |
| Adaptive local hyperplane classification T Yang, V Kecman Neurocomputing 71 (13-15), 3001-3004, 2008 | 78 | 2008 |
| Learning and soft computing-support vector machines, neural networks, fuzzy logic systems V Kecman Neural Networks, Fuzzy Logic Systems, The MIT Press, Cambridge, MA, 2001 | 74 | 2001 |
| A data mining approach to financial time series modelling and forecasting Z Vojinovic, V Kecman, R Seidel Intelligent Systems in Accounting, Finance & Management 10 (4), 225-239, 2001 | 66 | 2001 |
| Parallel multitask cross validation for support vector machine using GPU Q Li, R Salman, E Test, R Strack, V Kecman Journal of Parallel and Distributed Computing 73 (3), 293-302, 2013 | 65 | 2013 |
| Support vector machines: theory and applications V Kecman, L Wang Springer-Verlag Berlin Heidelberg, 2005 | 60 | 2005 |
| A chunking method for euclidean distance matrix calculation on large dataset using multi-gpu Q Li, V Kecman, R Salman 2010 Ninth International Conference on Machine Learning and Applications …, 2010 | 58 | 2010 |
| Optimal control: weakly coupled systems and applications Z Gajic, MT Lim, D Skataric, WC Su, V Kecman CRC Press, 2018 | 57 | 2018 |
| Margin-based ensemble classifier for protein fold recognition T Yang, V Kecman, L Cao, C Zhang, JZ Huang Expert Systems with Applications 38 (10), 12348-12355, 2011 | 53 | 2011 |
| Regression as classification R Salman, V Kecman 2012 Proceedings of IEEE Southeastcon, 1-6, 2012 | 51 | 2012 |
Qi LiVirginia Commonwealth UniversityPotvrđena adresa e-pošte na vcu.edu
