Fazekas István

University of Debrecen Faculty of Informatics

Department of Applied Mathematics and Probability

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Uploaded publications:

104

Publications in DEA:

OA:

Date range:

1984-2026

2026

Masasila, N. H., Fazekas, I.: Strong law of large numbers for [phi]-sub-Gaussian random variables under sub-linear expectation spaces.
Probab. Uncertain. Quant. Risk. [Submitted], 1-10, 2026.

DEA

Masasila, N. H., Fazekas, I.: Strong Laws of Large Numbers for General Random Variables Under Conditional Sub-Additive Expectation and Capacity.
Mathematics. 14 (5), 1-19, (article identifier: 775), 2026.

doi DEA

Journal metrics:

Q2 Computer Science (miscellaneous) (2024)

Q2 Engineering (miscellaneous) (2024)

Q2 Mathematics (miscellaneous) (2024)

2025

Fazekas, I., Fórián, L.: A family of network evolution models with moderate density.
Stat. Pap. 66 (5), 1-18, (article identifier: 105), 2025.

doi DEA WoS

Journal metrics:

Q2 Statistics and Probability (2024)

Q2 Statistics, Probability and Uncertainty (2024)

Fazekas, I., Masasila, N. H.: Explicit rate of convergence in strong laws of large numbers for random variables with double indices.
In: The Mediterranean International Conference of Pure & Applied Mathematics and Related Areas : Proceedings book of MICOPAM2025. Szerk.: Mustafa Alkan, Irem Kucukoglu, Ortaç Öneş, et. al, Josip Juraj Strossmayer University of Osijek, Osijek, 200, 2025. ISBN: 9789534691502

DEA

Fazekas, I., Fazekas, B., Suja, M. O.: Limit theorems for runs containing two types of contaminations.
Period. Math. Hung. 90 (1), 78-93, 2025.

doi DEA WoS Scopus

Journal metrics:

Q3 Mathematics (miscellaneous) (2024)

Fazekas, I., Fazekas, B., Fórián, L.: On the Convergence Rate for the Longest at Most T-Contaminated Runs of Heads.
Entropy. 27 (1), 1-9, (article identifier: 33), 2025.

doi DEA

Journal metrics:

Q2 Electrical and Electronic Engineering (2024)

Q2 Information Systems (2024)

Q2 Mathematical Physics (2024)

Q2 Physics and Astronomy (miscellaneous) (2024)

Fazekas, I., Masasila, N. H.: Quantitative strong laws of large numbers for random variables with double indices.
Ann. Math. Inform. 62, 55-65, 2025.

doi DEA WoS

Journal metrics:

Q4 Computer Science (miscellaneous) (2024)

Q4 Mathematics (miscellaneous) (2024)

2024

Fazekas, I., Barta, A., Fórián, L., Porvázsnyik, B.: A continuous-time network evolution model describing N-interactions.
MATH. 9 (12), 35721-35742, 2024.

doi DEA WoS Scopus

Journal metrics:

Q2 Mathematics (miscellaneous)

Fazekas, I., Masasila, N. H.: A general approach to conditional strong laws of large numbers.
Annales Universitat. Mariae Curie-Sklodowska, A - Math. 78 (1), 27-35, 2024.

doi DEA Scopus

Journal metrics:

Q4 Applied Mathematics

Q4 Algebra and Number Theory

Q4 Analysis

Q4 Statistics and Probability

10.

Fazekas, I., Fazekas, B., Suja, M. O.: A limit theorem for runs containing two types of contaminations.
Period. Math. Hung. 90 (1), 78-93, 2024.

doi DEA WoS Scopus

Journal metrics:

Q3 Mathematics (miscellaneous)

11.

Fazekas, I., Fazekas, B., Suja, M. O.: Convergence rate for the longest T-contaminated runs of heads.
Stat. Probab. Lett. 208, 1-8, 2024.

doi DEA WoS Scopus

Journal metrics:

Q2 Statistics and Probability

Q3 Statistics, Probability and Uncertainty

2023

12.

Fazekas, I., Barta, A., Noszály, C., Porvázsnyik, B.: A continuous-time network evolution model describing 3-interactions.
Commun. Stat.-Theory Methods. 52 (11), 4001-4020, 2023.

doi DEA WoS Scopus

Journal metrics:

Q3 Statistics and Probability

13.

Fazekas, I., Fórián, L., Barta, A.: Deep Learning from Noisy Labels with Some Adjustments of a Recent Method.
Infocommun. J. 15 (Special), 9-12, 2023.

doi DEA WoS Scopus

Journal metrics:

Q3 Computer Science (miscellaneous)

Q3 Electrical and Electronic Engineering

2022

14.

Fazekas, I.: 2022 IEEE 2nd Conference on Information Technology and Data Science (CITDS): Proceedings: May 16-18, 2022. : Online on CISCO Webex platform.
Institute of Electrical and Electronics Engineers (IEEE), Piscataway, 337 p., 2022. ISBN: 9781665496537

DEA

15.

Čuprunov, A., Fazekas, I.: On the Numbers of Particles in Cells in an Allocation Scheme Having an Even Number of Particles in Each Cell.
Mathematics. 10, 1-22, 2022.

doi DEA WoS Scopus

Journal metrics:

Q2 Computer Science (miscellaneous)

Q2 Engineering (miscellaneous)

Q2 Mathematics (miscellaneous)

2021

16.

Fazekas, I., Barta, A.: A Continuous-Time Network Evolution Model Describing 2- and 3-Interactions.
Mathematics. 9 (23), 1-26, (article identifier: 3143), 2021.

doi DEA WoS Scopus

Journal metrics:

Q2 Computer Science (miscellaneous)

Q2 Engineering (miscellaneous)

Q2 Mathematics (miscellaneous)

17.

Fazekas, I., Barta, A., Fórián, L.: Ensemble noisy label detection on MNIST.
Ann. Math. Inform. 53, 125-137, 2021.

doi DEA WoS Scopus

Journal metrics:

Q3 Computer Science (miscellaneous)

Q4 Mathematics (miscellaneous)

18.

Fazekas, I., Suja, M. O.: Limit theorems for contaminated runs of heads.
Ann. Univ. Sci. Budapest, Sect. Comp. 52, 131-146, 2021.

DEA

19.

Fazekas, I., Barta, A.: Theoretical and simulation results for a 2-type network evolution model.
In: Proceedings of the 1st Conference on Information Technology and Data Science. Ed.: István Fazekas, András Hajdu, Tibor Tómács, CEUR Workshop Proceedings, Debrecen, 104-114, 2021, (CEUR Workshop Proceedings, ISSN 1613-0073 ; 2874.)

DEA Scopus

2020

20.

Fazekas, I., Pecsora, S.: Numerical results on noisy blown-up matrices.
Ann. Math. Inform. 51, 17-28, 2020.

doi DEA WoS Scopus

Journal metrics:

Q4 Computer Science (miscellaneous)

Q4 Mathematics (miscellaneous)

21.

Čuprunov, A., Fazekas, I.: On the number of empty cells in the allocation scheme of indistinguishable particles.
Annales Universitatis Mariae Curie-Sklodowska A Math. 74 (1), 15-29, 2020.

doi DEA

22.

Fazekas, I., Pecsora, S.: On the spectrum of noisy blown-up matrices.
Special Matrices. 8 (1), 104-122, 2020.

doi DEA WoS Scopus

Journal metrics:

Q2 Algebra and Number Theory

Q2 Geometry and Topology

23.

Fazekas, I., Barta, A., Noszály, C.: Simulation results on a triangle-based network evolution model.
Ann. Math. Inform. 51, 7-15, 2020.

doi DEA WoS Scopus

Journal metrics:

Q4 Computer Science (miscellaneous)