13133 / 13168 - Machine Learning

Publications 2016

Papers in WoS Journals

MRAZ, F., F. OTTO, and D. PRŮŠA. Some Classes of Rational Functions for Pictures. RAIRO - Theoretical Informatics and Applications. 2016, 50(4), 351-369. ISSN 0988-3754. DOI 10.1051/ita/2016025.

BRESLER, M., D. PRŮŠA, and V. HLAVÁČ. Online recognition of sketched arrow-connected diagrams. International Journal on Document Analysis and Recognition. 2016, 19(3), 253-267. ISSN 1433-2833. DOI 10.1007/s10032-016-0269-z.

BIKCHENTAEV, A and M. NAVARA. States on symmetric logics: extensions. Mathematica Slovaca. 2016, 66(2), 359-366. ISSN 0139-9918. DOI 10.1515/ms-2015-0141.

PRŮŠA, D. Non-recursive trade-offs between two-dimensional automata and grammars. Theoretical Computer Science. 2016, 610 121-132. ISSN 0304-3975. DOI 10.1016/j.tcs.2015.05.033.

Conference Proceedings

SIXTA, T. and B. FLACH. Multiple Object Segmentation and Tracking by Bayes Risk Minimization. In: OURSELIN, S., et al., eds. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, Part II. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, Athens, 2016-10-17/2016-10-21. Cham: Springer International Publishing, 2016. p. 607-615. Lecture Notes in Computer Science. vol. 9901. ISSN 0302-9743. ISBN 978-3-319-46722-1. DOI 10.1007/978-3-319-46723-8_70.

GAGOLA III, S.M., J. GABRIËLS, and M. NAVARA. Operations in orthomodular lattices and the role of Sasaki projection. In: Applications of Algebra 20. Zakopane, 2016-03-07/2016-03-13. Czestochowa: Jan Dlugosz University, 2016. p. 38-40.

BARTOŠ, K., M. SOFKA, and V. FRANC. Optimized Invariant Representation of Network Traffic for Detecting Unseen Malware Variants. In: Proceedings of the 25th USENIX Security Symposium. 25th USENIX Security Symposium, Austin, Texas, 2016-08-10/2016-08-12. The USENIX Association, 2016. p. 807-822. ISBN 978-1-931971-32-4. Available from: https://www.usenix.org/system/files/conference/usenixsecurity16/sec16_paper_bartos.pdf

NAVARA, M. Axiomatic approach to probability of fuzzy events. In: DE BAETS, B., et al., eds. Functional Equations and Inequalities. Linz, 2016-02-02/2016-02-06. Linz: Universitätsdirektion, Johannes Kepler University, 2016. p. 66-72.

BARTOS, K., M. SOFKA, and V. FRANC. Learning Invariant Representation for Malicious Network Traffic Detection. In: European Conference on Artificial Intelligence. 22nd European Conference on Artificial Intelligence, Hague, 2016-08-29/2016-09-02. Amsterdam: IOS Press, 2016. p. 1132-1139. Frontiers in Artificial Intelligence and Applications. vol. 285. ISSN 0922-6389. ISBN 978-1-61499-671-2. DOI 10.3233/978-1-61499-672-9-1132.

NAVARA, M. Structure of orthoalgebras. In: 13th Biennial IQSA Meeting Quantum Structures 2016. Leicester, 2016-07-11/2016-07-15. Leicester: University of Leicester, 2016. p. 1-2.

PRŮŠA, D. Complexity of sets of two-dimensional patterns. In: SALOMAA, K. and Y.-S. HAN, eds. CIAA 2016: Proceedings of the 21st International Conference on Implementation and Application of Automata. 21st International Conference on Implementation and Application of Automata, Seoul, 2016-07-19/2016-07-22. Heidelberg: Springer-Verlag, GmbH, 2016. p. 236-247. Lecture Notes in Computer Science. ISSN 0302-9743. ISBN 978-3-319-40945-0. DOI 10.1007/978-3-319-40946-7_20.

NAVARA, M. MV-algebras and states on tribes. In: Many-Valued Logic: Algebraic, Geometric and Computational Aspects. Milano, 2016-09-26/2016-09-27. Milano: Universitia degli Studi di Milano, 2016. p. 1-2.

NAVARA, M. Continuity and axioms of probability of fuzzy events. In: AVALLONE, A., ed. Workshop on Effect Algebras, Boolean Algebras & Related Topics. Udine, 2016-01-25/2016-01-27. Udine: University of Udine, 2016. Available from: http://digilander.libero.it/udine2016/abstracts/navara.pdf

Dissertations

BRESLER, M. Understanding Formal Arrow-Connected Diagrams and Free-form Sketches. Praha: Defense date 2016-12-19. PhD Thesis. ČVUT FEL, Katedra kybernetiky - Centrum strojového vnímání. Supervised by D. PRŮŠA and V. HLAVÁČ.

Research Reports

FRANC, V., et al. Learning data discretization via convex optimization. [Research Report] Praha: ČVUT FEL, Katedra kybernetiky - Centrum strojového vnímání, 2016. Report no. CTU--CMP--2016--01. ISSN 1213-2365.