Vojislav Kecman
Affiliations: | Computer Science | Virginia Commonwealth University, Richmond, VA, United States |
Area:
Computer Science, Information TechnologyGoogle:
"Vojislav Kecman"
BETA: Related publications
See more...
Publications
You can help our author matching system! If you notice any publications incorrectly attributed to this author, please sign in and mark matches as correct or incorrect. |
Melki G, Kecman V, Ventura S, et al. (2018) OLLAWV: OnLine Learning Algorithm using Worst-Violators Applied Soft Computing. 66: 384-393 |
Melki G, Cano A, Kecman V, et al. (2017) Multi-Target Support Vector Regression Via Correlation Regressor Chains Information Sciences. 415: 53-69 |
Kecman V. (2016) Fast online algorithm for nonlinear support vector machines and other alike models Optical Memory and Neural Networks. 25: 203-218 |
Kecman V, Melki G. (2016) Fast online algorithms for Support Vector Machines Conference Proceedings - Ieee Southeastcon. 2016 |
Melki G, Kecman V. (2016) Speeding up online training of L1 Support Vector Machines Conference Proceedings - Ieee Southeastcon. 2016 |
Pokrajac D, Lazarevic A, Kecman V, et al. (2015) Automatic classification of laser-induced breakdown spectroscopy (LIBS) data of protein biomarker solutions Applied Spectroscopy. 68: 1067-1075 |
Kecman V. (2015) Iterative k Data Algorithm for solving both the least squares SVM and the system of linear equations Conference Proceedings - Ieee Southeastcon. 2015 |
Zigic L, Kecman V. (2014) Direct L2 Support Vector Machine classifier and performances of its two implementations Conference Proceedings - Ieee Southeastcon |
Kecman V, Zigic L. (2014) Algorithms for direct L2 support vector machines Inista 2014 - Ieee International Symposium On Innovations in Intelligent Systems and Applications, Proceedings. 419-424 |
Zigic L, Kecman V. (2014) Variants and performances of novel direct learning algorithms for L2 support vector machines Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8468: 82-91 |