13136 / 13143 - Publications - 2022

13136 / 13143 - Intelligent Data Analysis

Publications 2022

Papers in WoS Journals

AI, J., O. KUŽELKA, and Y. WANG. Hoeffding and Bernstein Inequalities for U-statistics without Replacement. Statistics and Probability Letters. 2022, 187 ISSN 0167-7152. DOI 10.1016/j.spl.2022.109528.

BERGOU, E.H., et al. A Stochastic Levenberg--Marquardt Method Using Random Models with Complexity Results. SIAM/ASA Journal on Uncertainty Quantification. 2022, 10(1), 507-536. ISSN 2166-2525. DOI 10.1137/20M1366253. Available from: https://epubs.siam.org/doi/epdf/10.1137/20M1366253

KAISRLIKOVA, M., et al. RUNX1 Mutations Contribute to the Progression of MDS Due to Disruption of Antitumor Cellular Defense: A Study on Patients with Lower-risk MDS. LEUKEMIA. 2022, 1898-1906. ISSN 0887-6924. DOI 10.1038/s41375-022-01584-3.

KUNGURTSEV, V. Distributed Stochastic Nonsmooth Nonconvex Optimization. Operations Research Letters. 2022, 50(6), 627-631. ISSN 0167-6377. DOI 10.1016/j.orl.2022.09.001.

HUBÁČEK, O., G. ŠOUREK, and F. ŽELEZNÝ. Forty years of score-based soccer match outcome prediction: an experimental review. IMA Journal of Management Mathematics. 2022, 33(1), 1-18. ISSN 1471-678X. DOI 10.1093/imaman/dpab029.

IATSIUK, V., et al. Semantic Clustering Analysis of E3-ubiquitin Ligases in Gastrointestinal Tract Defines Genes Ontology Clusters with Tissue Expression Patterns. BMC GASTROENTEROLOGY. 2022, 22(1), ISSN 1471-230X. DOI 10.1186/s12876-022-02265-2. Available from: https://bmcgastroenterol.biomedcentral.com/articles/10.1186/s12876-022-02265-2

SIMA, M., et al. The Impact of Extractable Organic Matter from Gasoline and Alternative Fuel Emissions on Bronchial Cell Models. Toxicology in Vitro. 2022, 80 ISSN 0887-2333. DOI 10.1016/j.tiv.2022.105316.

KUMAR, N., O. KUŽELKA, and L.D. RAEDT. Learning Distributional Programs for Relational Autocompletion. Theory and Practice of Logic Programming. 2022, 22(1), 81-114. ISSN 1471-0684. DOI 10.1017/S1471068421000144.

MATIAS, J., V. KUNGURTSEV, and M. EGAN. Simultaneous Online Model Identification and Production Optimization Using Modifier Adaptation. Journal of Process Control. 2022, 110 110-120. ISSN 0959-1524. DOI 10.1016/j.jprocont.2021.12.009.

MERKEROVA, M.D., et al. Noncoding RNAs and Their Response Predictive Value in Azacitidine-treated Patients With Myelodysplastic Syndrome and Acute Myeloid Leukemia With Myelodysplasia-related Changes. Cancer Genomics & Proteomics. 2022, 19(2), 205-228. ISSN 1109-6535. DOI 10.21873/cgp.20315.

RYŠAVÝ, P., J. KLÉMA, and M. MERKEROVÁ. circGPA: circRNA functional annotation based on probability-generating functions. BMC Bioinformatics. 2022, 2022(23), 392-414. ISSN 1471-2105. DOI 10.1186/s12859-022-04957-8. Available from: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-022-04957-8

FACHINEI, F., et al. Diminishing Stepsize Methods for Nonconvex Composite Problems Via Ghost Penalties: From the General to the Convex Regular Constrained Case. Optimization Methods and Software. 2022, 37(4), 1242-1268. ISSN 1055-6788. DOI 10.1080/10556788.2020.1854253.

Papers in Other Journals

AMBROZ, A., et al. Oxidative Stress and Antioxidant Response in Populations of the Czech Republic Exposed to Various Levels of Environmental Pollutants. International Journal of Environmental Research and Public Health. 2022, 19(6), ISSN 1660-4601. DOI 10.3390/ijerph19063609. Available from: https://www.mdpi.com/1660-4601/19/6/3609/htm

BERGOU, E., et al. A Subsampling Line-Search Method with Second-Order Results. INFORMS JOURNAL ON OPTIMIZATION. 2022, 4(4), 403-425. ISSN 2575-1484. DOI 10.1287/ijoo.2022.0072.

SCHEVCHENKO, A., V. KUNGURTSEV, and M. MONDELLI. Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks. Journal of Machine Learning Research. 2022, 23(130), 1-55. ISSN 1532-4435. DOI 10.48550/arXiv.2111.02278.

Books, Book Chapters and Lecture Notes

ŠÍR, G. Deep Learning with Relational Logic Representations. Amsterdam: IOS Press, 2022. ISSN 1879-8314. ISBN 978-1-64368-343-0.

Conference Proceedings

JUNG, P. and O. KUŽELKA. Graph Generation with Graphon Generative Adversarial Networks. In: Proceedings of The 31st International Conference on Inductive Logic Programming. 31st International Conference on Inductive Logic Programming, Cumberland Lodge, 2022-09-28/2022-09-30. Proceedings of Machine Learning Research, 2022.

ŠÍR, G., F. ŽELEZNÝ, and O. KUŽELKA. Learning with Molecules beyond Graph Neural Networks. In: GRAPHS AND MORE COMPLEX STRUCTURES FOR LEARNING AND REASONING workshop @ AAAI. Massachusetts: OpenReview.net / University of Massachusetts, 2022. Available from: https://sites.google.com/view/gclr2022/accepted-papers

BARVÍNEK, J., et al. Automatic Conjecturing of P-Recursions Using Lifted Inference. In: Inductive Logic Programming. 30th International Conference on Inductive Logic Programming, Virtual - Online, 2021-10-25/2021-10-27. Springer Science and Business Media Deutschland GmbH, 2022. p. 17-25. ISSN 0302-9743. ISBN 978-3-030-97453-4. DOI 10.1007/978-3-030-97454-1_2.

KUNC, V. and J. KLÉMA. On Functional Annotation with Gene Co-expression Networks. In: Proceedings of The 2022 IEEE International Conference on Bioinformatics and Biomedicine. 2022 IEEE International Conference on Bioinformatics and Biomedicine, Las Vegas, 2022-12-06/2022-12-08. IEEE Xplore, 2022. p. 3055-3062. ISBN 978-1-6654-6819-0. DOI 10.1109/BIBM55620.2022.9995542. Available from: https://ieeexplore.ieee.org/document/9995542

SVATOŠ, M., et al. Learning to Generate Molecules From Small Datasets Using Neural Markov Logic Networks. In: International Joint Conference on Learning & Reasoning. Cumberland Lodge, The Great Park Windsor, 2022-09-28/2022-09-30. Cham: Springer, 2022.

KRISHNAMOORTHY, D. and V. KUNGURTSEV. A Sensitivity Assisted Alternating Directions Method of Multipliers for Distributed Optimization. In: Proceedings of 61st IEEE Conference on Decision and Control. 61st IEEE Conference on Decision and Control, Cancún, 2022-12-06/2022-12-09. Piscataway: IEEE, 2022. p. 295-300. ISSN 2576-2370. ISBN 978-1-6654-6761-2. DOI 10.1109/CDC51059.2022.9993352. Available from: https://ieeexplore.ieee.org/abstract/document/9993352

WANG, Y., et al. Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence. 36th AAAI Conference on Artificial Intelligence (AAAI-22), - virtual, 2022-02-22/2022-03-01. Menlo Park: AAAI Press, 2022. p. 10070-10079. ISSN 2159-5399. ISBN 978-1-57735-876-3. DOI 10.1609/aaai.v36i9.21246.

The page was created 28.03.2024 05:00:01
Responsible person: RNDr. Patrik Mottl, Ph.D.