Jelena Slivka

Jelena Slivka is an assistant professor in the Department of Computing and Control, Faculty of Technical Sciences, University of Novi Sad since 2015.

She received her M.Sc. (Integrated Undergraduate Academic and Graduate Academic - Master) degree in 2008 and a Ph.D. degree in 2014, all in Computer Science from the University of Novi Sad, Faculty of Technical Sciences.

Since 2008 she is with the Faculty of Technical Science in Novi Sad. She published over ten papers and participated in 2 projects. Jelena Slivka serves or has served as a programme committee member for ICIST (International Conference on Information Society and Technology) and YU Info conference.

Her research interests include data mining and machine learning.

Courses

Machine Learning
Oral and written communication skills

Current Research

- Semi-supervised learning, with a focus on co-training algorithm;

Selected Publications

  1. Slivka, J., Sladić, G., Branko, M., Kovačević, A., RSSalg software: a tool for flexible experimenting with co-training based semi-supervised algorithms, Knowledge-Based Systems, DOI 10.1016/j.knosys.2017.01.024, http://www.sciencedirect.com/science/article/pii/S0950705117300357
  2. Slivka, J., Kovačević, A, Konjović, Z, Combining co-training with ensemble learning for application on single-view natural language datasets, Acta Polytechnica Hungarica, Vol. 10, No 2, pp. 133-152, 2013. ISSN 1785-8860
  3. Slivka, J., Ping, Z., Kovačević, A, Konjović, Z., Obradović, Z., Semi-Supervised Learning on Single-View Datasets by Integration of Multiple Co-trained Classifiers, Proceedings of the 11th International Conference on Machine Learning and Applications (ICMLA), Boca Raton: The institute of Electrical and Electronic Engineers, Inc., 12-15 December, 2012., pp. 458-464, ISBN 978-0-7695-4913-2
  4. Slivka, J., Nikolic, M., Ristovski, K., Radosavljevic, V. and Obradovic, Z., 2014. Distributed Gaussian Conditional Random Fields Based Regression for Large Evolving Graphs. In Proc. 14th SIAM Int’l Conf. Data Mining, Workshop on Mining Networks and Graphs