13133 / 13168 - Machine Learning

Publications 2024

Papers in WoS Journals

DLASK, T. Projection methods for finding the greatest element of the intersection of max-closed convex sets. Annals of Operations Research. 2024, 340(2-3), 811-836. ISSN 0254-5330. DOI 10.1007/s10479-024-05980-z.

DLASK, T. and T. WERNER. Using Constraint Propagation to Bound Linear Programs. Journal of Artificial Intelligence Research. 2024, 80 665-718. ISSN 1076-9757. DOI 10.1613/jair.1.15604.

NAVARA, M. and K. SVOZIL. Form of contextuality predicting probabilistic equivalence between two sets of three mutually noncommuting observables. PHYSICAL REVIEW A. 2024, 109(2), ISSN 2469-9934. DOI 10.1103/PhysRevA.109.022222. Available from: https://journals.aps.org/pra/accepted/d0078N41Wb41192e65a020e14a7dc99ffd3ccc6fc

Papers in Other Journals

HOUŠKOVÁ, K. and M. NAVARA. Geometry of generators of triangular norms and copulas. Dependence Modeling. 2024, 12(1), ISSN 2300-2298. DOI 10.1515/demo-2024-0004. Available from: https://www.degruyter.com/document/doi/10.1515/demo-2024-0004/html

Conference Proceedings

PRŮŠA, D. and V. FRANC. Constrained Binary Decision Making. In: Advances in Neural Information Processing Systems 37 (NeurIPS 2024). NeurIPS 2024 The Thirty-Eighth Annual Conference on Neural Information Processing Systems, Vancouver, 2024-12-10/2024-12-15. Neural Information Processing Systems Foundation, Inc., 2024. vol. 37. ISSN 1049-5258. ISBN 9798331314385. Available from: https://papers.nips.cc/paper_files/paper/2024/hash/6ffc307731cd1d6784c35c6c2875c122-Abstract-Conference.html

BUREŠOVÁ, D., et al. Existence of Reichenbach's common cause. In: Quantum Structures 2024. Book of Abstracts. Quantum Structures 2024, Brussels, 2024-07-22/2024-07-26. Brussel: Vrije Universiteit Brussel, 2024. Available from: https://www.dropbox.com/scl/fi/t37qc5zerm6xbnc11h2jw/BOA_IQSA24.pdf?rlkey=3h4wv5ursxjk5odyklvo21ybz&e=1&dl=0

FLACH, B., D. SCHLESINGER, and O. SHEKHOVTSOV. Symmetric Equilibrium Learning of VAEs. In: Proc. of the International Conference on Artificial Intelligence and Statistics. 27th International Conference on Artificial Intelligence and Statistics, Valencia, 2024-05-02/2024-05-04. Proceedings of Machine Learning Research, 2024. p. 3214-3222. PMLR. vol. 238. ISSN 2640-3498. Available from: https://proceedings.mlr.press/v238/flach24a.html

NAVARA, M. and K. SVOZIL. Pseudocomplemented-like orthomodular posets. In: Quantum Structures 2024. Book of Abstracts. Quantum Structures 2024, Brussels, 2024-07-22/2024-07-26. Brussel: Vrije Universiteit Brussel, 2024. Available from: https://www.dropbox.com/scl/fi/t37qc5zerm6xbnc11h2jw/BOA_IQSA24.pdf?rlkey=3h4wv5ursxjk5odyklvo21ybz&e=1&dl=0

PAPLHÁM, J. and V. FRANC. A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark. In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Seattle, 2024-06-16/2024-06-22. Los Alamitos: IEEE Computer Society, 2024. p. 1196-1205. ISSN 1063-6919. ISBN 979-8-3503-5301-3. DOI 10.1109/CVPR52733.2024.00120.

NAVARA, M. and A. POPOVIČ. Approximations using triangular norms. In: STUPŇANOVÁ, A., M. DYBA, and V. PAVLISKA, eds. FSTA 2024 Book of Abstracts. The Seventeenth International Conference on Fuzzy Set Theory and Applications, Liptovský Ján, 2024-01-28/2024-02-02. University of Ostrava, 2024. p. 37-38. Available from: https://www.fsta.sk/materials/fsta2024bookofabstracts.pdf

HOUŠKOVÁ, K. and M. NAVARA. Uniqueness of generators is what we need. In: STUPŇANOVÁ, A., M. DYBA, and V. PAVLISKA, eds. FSTA 2024 Book of Abstracts. The Seventeenth International Conference on Fuzzy Set Theory and Applications, Liptovský Ján, 2024-01-28/2024-02-02. University of Ostrava, 2024. p. 68-69. Available from: https://www.fsta.sk/materials/fsta2024bookofabstracts.pdf

VORÁČEK, V. and T. WERNER. Convergence of Some Convex Message Passing Algorithms to a Fixed Point. In: Proceedings of Machine Learning Research. ICML2024: International Conference on Machine Learning, Vienna, 2024-07-21/2024-07-27. Proceedings of Machine Learning Research, 2024. p. 49688-49697. vol. 235. ISSN 2640-3498. Available from: https://proceedings.mlr.press/v235/voracek24a.html