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Publications 2024

Papers in WoS Journals

BELLON, A., et al. Time-Varying Semidefinite Programming: Path Following a Burer–Monteiro Factorization. SIAM Journal on Optimization. 2024, 34(1), 1-26. ISSN 1052-6234. DOI 10.1137/22M1529762.

SIMA, M., et al. Gene Expression Profiles and Protein-protein Interaction Networks in THP-1 Cells Exposed to Metal-based Nanomaterials. Environmental Toxicology and Pharmacology. 2024, 108 ISSN 1382-6689. DOI 10.1016/j.etap.2024.104469.

KUNGURTSEV, V., et al. Iteration Complexity of Variational Quantum Algorithms. Quantum. 2024, 8 1-42. ISSN 2521-327X. DOI 10.22331/q-2024-10-10-1495. Available from: https://quantum-journal.org/papers/q-2024-10-10-1495/#

SIMOVÁ, Z., et al. Transcriptome Changes in Humans Acutely Exposed to Nanoparticles During Grinding of Dental Nanocomposites. Nanomedicine. 2024, 19(17), 1511-1523. ISSN 1743-5889. DOI 10.1080/17435889.2024.2362611.

WANG, Y., et al. Lifted Algorithms for Symmetric Weighted First-order Model Sampling. Artificial Intelligence. 2024, 331 ISSN 0004-3702. DOI 10.1016/j.artint.2024.104114.

JUNG, P., G. MARRA, and O. KUŽELKA. Quantified Neural Markov Logic Networks. International Journal of Approximate Reasoning. 2024, 171 ISSN 0888-613X. DOI 10.1016/j.ijar.2024.109172.

DIOUANE, Y., et al. Inexact Direct-search Methods for Bilevel Optimization Problems. Computational Optimization and Applications. 2024, 88(2), 469-490. ISSN 0926-6003. DOI 10.1007/s10589-024-00567-7.

Papers in Other Journals

KUNC, V. and J. KLÉMA. Three Decades of Activations: A Comprehensive Survey of 400 Activation Functions for Neural Networks. Machine Learning. 2024, 1-107. ISSN 0885-6125. DOI 10.48550/arXiv.2402.09092.

Conference Proceedings

HORČÍK, R. and G. ŠÍR. Expressiveness of Graph Neural Networks in Planning Domains. In: Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling. The 34th International Conference on Automated Planning and Scheduling (ICAPS 2024), Banff, 2024-06-01/2024-06-06. Menlo Park, California: AAAI Press, 2024. p. 281-289. ISSN 2334-0843. ISBN 978-1-57735-889-3. DOI 10.1609/icaps.v34i1.31486. Available from: https://ojs.aaai.org/index.php/ICAPS/article/view/31486

CHATTERJEE, B., V. KUNGURTSEV, and D. ALISTRAH. Federated SGD with Local Asynchrony. In: 2024 IEEE 44th International Conference on Distributed Computing Systems. 44th International Conference on Distributed Computing Systems, New Jersy, 2024-07-23/2024-07-26. IEEE Xplore, 2024. p. 857-868. ISSN 2575-8411. ISBN 979-8-3503-8605-9. DOI 10.1109/ICDCS60910.2024.00084. Available from: https://ieeexplore.ieee.org/abstract/document/10631076

MENG, Q., et al. A More Practical Algorithm for Weighted First-Order Model Counting with Linear Order Axiom. In: Frontiers in Artificial Intelligence and Applications. 27TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE, Santiago de Compostela, 2024-10-19/2024-10-24. Oxford: IOS Press, 2024. p. 3145-3154. ISSN 0922-6389. DOI 10.3233/FAIA240858.

TÓTH, J. and O. KUŽELKA. Complexity of Weighted First-Order Model Counting in the Two-Variable Fragment with Counting Quantifiers: A Bound to Beat. In: Proceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning. 21st International Conference on Principles of Knowledge Representation and Reasoning, Hanoi, 2024-11-02/2024-11-08. International Joint Conferences on Artificial Intelligence Organization, 2024. p. 676-686. ISSN 2334-1033. ISBN 978-1-956792-05-8. DOI 10.24963/kr.2024/64.

SAEED VAHIDIAN, Y., et al. Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents. In: Computer Vision – ECCV 2024. The 18th European Conference on Computer Vision, Milano, 2024-09-29/2024-10-04. Springer Nature, 2024. p. 18-33. ISBN 978-3-031-73228-7. DOI 10.1007/978-3-031-73229-4_2.