@{MTMT:35076182,
	title = {Anomaly Detection Using Logs},
	url = {https://m2.mtmt.hu/api/publication/35076182},
	author = {Szilágyi, Péter and Horváth, Gábor and Attila, KADAR},
	unique-id = {35076182},
	year = {2024},
	orcid-numbers = {Horváth, Gábor/0000-0003-3097-1273}
}

@article{MTMT:32242266,
	title = {Correction to: Transient analysis of piecewise homogeneous Markov fluid models (Annals of Operations Research, (2020), 10.1007/s10479-020-03831-1)},
	url = {https://m2.mtmt.hu/api/publication/32242266},
	author = {Almousa, Salah Al-Deen Afif Said and Horváth, Gábor and Telek, Miklós},
	doi = {10.1007/s10479-021-03934-3},
	journal-iso = {ANN OPER RES},
	journal = {ANNALS OF OPERATIONS RESEARCH},
	volume = {332},
	unique-id = {32242266},
	issn = {0254-5330},
	abstract = {Affiliation for author Miklos Telek was missing in the original publication and should be read as: Department of Networked Systems and Services, Budapest University of Technology and Economics, Budapest, Hungary and MTA-BME Information Systems Reseach Group, Hungary. Along with Department of Networked Systems and Services, Budapest University of Technology and Economics, Budapest, Hungary. Original article has been updated. © 2021, Springer Science+Business Media, LLC, part of Springer Nature.},
	year = {2024},
	eissn = {1572-9338},
	pages = {1251-1251},
	orcid-numbers = {Horváth, Gábor/0000-0003-3097-1273; Telek, Miklós/0000-0001-9600-6084}
}

@book{MTMT:35076205,
	title = {Method and Apparatus for Anomaly Detection},
	url = {https://m2.mtmt.hu/api/publication/35076205},
	author = {Szilágyi, Péter and Horváth, Gábor and Attila, KADAR},
	unique-id = {35076205},
	year = {2023},
	orcid-numbers = {Horváth, Gábor/0000-0003-3097-1273}
}

@article{MTMT:33879816,
	title = {TeleDAL: a regression-based template-less unsupervised method for finding anomalies in log sequences},
	url = {https://m2.mtmt.hu/api/publication/33879816},
	author = {Horváth, Gábor and Mészáros, András Gergely and Szilágyi, Péter},
	doi = {10.1007/s11227-023-05379-w},
	journal-iso = {J SUPERCOMPUT},
	journal = {JOURNAL OF SUPERCOMPUTING},
	volume = {79},
	unique-id = {33879816},
	issn = {0920-8542},
	year = {2023},
	eissn = {1573-0484},
	pages = {18394-18416},
	orcid-numbers = {Horváth, Gábor/0000-0003-3097-1273}
}

@article{MTMT:33794293,
	title = {The Sub-Sequence Summary Method for Detecting Anomalies in Logs},
	url = {https://m2.mtmt.hu/api/publication/33794293},
	author = {Horváth, Gábor and Kádár, Attila and Szilágyi, Péter},
	doi = {10.1109/ACCESS.2023.3266990},
	journal-iso = {IEEE ACCESS},
	journal = {IEEE ACCESS},
	volume = {11},
	unique-id = {33794293},
	issn = {2169-3536},
	year = {2023},
	eissn = {2169-3536},
	pages = {37412-37423},
	orcid-numbers = {Horváth, Gábor/0000-0003-3097-1273; Kádár, Attila/0009-0007-8798-950X}
}

@article{MTMT:33629258,
	title = {Bilateral-Weighted Online Adaptive Isolation Forest for anomaly detection in streaming data},
	url = {https://m2.mtmt.hu/api/publication/33629258},
	author = {Hannák, Gábor and Horváth, Gábor and Kádár, Attila and Szalai, Márk Dániel},
	doi = {10.1002/sam.11612},
	journal-iso = {STAT ANAL DATA MIN},
	journal = {STATISTICAL ANALYSIS AND DATA MINING},
	volume = {16},
	unique-id = {33629258},
	issn = {1932-1864},
	abstract = {We propose a method called Bilateral-Weighted Online Adaptive Isolation Forest (BWOAIF) for unsupervised anomaly detection based on Isolation Forest (IF), which is applicable to streaming data and able to cope with concept drift. Similar to IF, the proposed method has only few hyperparameters whose effect on the performance are easy to interpret by human intuition and therefore easy to tune. BWOAIF ingests data and classifies it as normal or anomalous, and simultaneously adapts its classifier by removing old trees as well as by creating new ones. We show that BWOAIF adapts gradually to slow concept drifts, and, at the same time, it is able to adapt fast to sudden changes of the data distribution. Numerical results show the efficacy of the proposed algorithm and its ability to learn different classes of concept drifts, such as slow/fast concept shift, concept split, concept appearance, and concept disappearance.},
	year = {2023},
	eissn = {1932-1872},
	pages = {215-223},
	orcid-numbers = {Hannák, Gábor/0000-0003-3586-8072; Horváth, Gábor/0000-0003-3097-1273}
}

@article{MTMT:33099054,
	title = {Parameter estimation of Markov modulated fluid arrival processes},
	url = {https://m2.mtmt.hu/api/publication/33099054},
	author = {Almousa, Salah Al-Deen Afif Said and Horváth, Gábor and Telek, Miklós},
	doi = {10.1016/j.peva.2022.102316},
	journal-iso = {PERFORM EVALUATION},
	journal = {PERFORMANCE EVALUATION},
	volume = {157-158},
	unique-id = {33099054},
	issn = {0166-5316},
	abstract = {Markov modulated discrete arrival processes have a wide literature, including parameter estimation methods based on expectation–maximization (EM). In this paper, we investigate the adaptation of these EM based methods to Markov modulated fluid arrival processes (MMFAP), and conclude that only the generator matrix of the modulating Markov chain of MMFAPs can be approximated by EM based method. For the rest of the parameters, the fluid rates and the fluid variances, we investigate the efficiency of numerical likelihood maximization.
		
		To reduce the computational complexity of the likelihood computation, we accelerate the numerical inverse Laplace transformation step of the procedure with function fitting.},
	year = {2022},
	eissn = {1872-745X},
	orcid-numbers = {Horváth, Gábor/0000-0003-3097-1273; Telek, Miklós/0000-0001-9600-6084}
}

@article{MTMT:32897098,
	title = {The CME method: Efficient numerical inverse Laplace transformation with Concentrated Matrix Exponential distribution},
	url = {https://m2.mtmt.hu/api/publication/32897098},
	author = {Almousa, Salah Al-Deen Afif Said and Horváth, Gábor and Horváth, Illés and Mészáros, András Gergely and Telek, Miklós},
	doi = {10.1145/3543146.3543155},
	journal-iso = {SIGMETR PERFORM EVAL REV},
	journal = {SIGMETRICS PERFORMANCE EVALUATION REVIEW},
	volume = {49},
	unique-id = {32897098},
	issn = {0163-5999},
	abstract = {Numerical inverse Laplace transformation (NILT) is an important tool in the field of system modelling and performance analysis. The recently introduced CME method has many important advantages over the alternative numerical inverse Laplace transformation (NILT) methods. It avoids Gibbs oscillation (i.e., does not generate overshoot and undershoot), preserves the monotonicity of functions, its accuracy is gradually improving with the order, and it is numerically more stable than the alternative methods. In this paper we demonstrate these advantages and introduce our tool which implements the CME method and other popular NILT methods.},
	year = {2022},
	eissn = {1557-9484},
	pages = {29-34},
	orcid-numbers = {Horváth, Gábor/0000-0003-3097-1273; Telek, Miklós/0000-0001-9600-6084}
}

@article{MTMT:31797535,
	title = {Transient analysis of piecewise homogeneous Markov fluid models},
	url = {https://m2.mtmt.hu/api/publication/31797535},
	author = {Almousa, Salah Al-Deen Afif Said and Horváth, Gábor and Telek, Miklós},
	doi = {10.1007/s10479-020-03831-1},
	journal-iso = {ANN OPER RES},
	journal = {ANNALS OF OPERATIONS RESEARCH},
	volume = {310},
	unique-id = {31797535},
	issn = {0254-5330},
	abstract = {Piecewise homogeneous Markov fluid models are composed by homogeneous intervals where the model is governed by an interval dependent pair of generators and the model behaviour changes at the boundaries. The main difficulty of the transient analysis of piecewise homogeneous Markov fluid models is the appropriate description of the various boundary cases. The paper proposes an analytical approach to handle the wide variety of the possible boundary cases in a relatively simple to describe and implement manner.},
	year = {2022},
	eissn = {1572-9338},
	pages = {333-353},
	orcid-numbers = {Horváth, Gábor/0000-0003-3097-1273; Telek, Miklós/0000-0001-9600-6084}
}

@article{MTMT:32801207,
	title = {EM Based Parameter Estimation for Markov Modulated Fluid Arrival Processes},
	url = {https://m2.mtmt.hu/api/publication/32801207},
	author = {Almousa, Salah Al-Deen Afif Said and Horváth, Gábor and Telek, Miklós},
	doi = {10.1007/978-3-030-91825-5_14},
	journal-iso = {LNCS},
	journal = {LECTURE NOTES IN COMPUTER SCIENCE},
	volume = {13104},
	unique-id = {32801207},
	issn = {0302-9743},
	abstract = {Markov modulated discrete arrival processes have a wide literature, including parameter estimation methods based on expectation-maximization (EM). In this paper, we investigate the adaptation of these EM based methods to Markov modulated fluid arrival processes (MMFAP), and conclude that only some parameters of MMFAPs can be approximated this way.},
	year = {2021},
	eissn = {1611-3349},
	pages = {226-242},
	orcid-numbers = {Horváth, Gábor/0000-0003-3097-1273; Telek, Miklós/0000-0001-9600-6084}
}