5 citations · 17 across the 9 of their papers we have counts for
10 papers
Limit theorems for runs containing two types of contaminations. Paper with detailed proofs
István Fazekas, Borbála Fazekas, Michael Ochieng Suja
In this paper, sequences of trials having three outcomes are studied. The outcomes are labelled as success, failure of type I and failure of type II. A run is called at most 1+1 co…
Diffusion-based Data Augmentation for Skin Disease Classification: Impact Across Original Medical Datasets to Fully Synthetic Images
Mohamed Akrout, Bálint Gyepesi, Péter Holló +9
Despite continued advancement in recent years, deep neural networks still rely on large amounts of training data to avoid overfitting. However, labeled training data for real-world…
Taylor's power law for the -stars network evolution model
István Fazekas, Csaba Noszály, Noémi Uzonyi
Taylor's power law states that the variance function decays as a power law. It is observed for population densities of species in ecology. For random networks another power law, th…
The -stars network evolution model
István Fazekas, Csaba Noszály, Attila Perecsényi
A new network evolution model is introduced in this paper. The model is based on co-operations of units. The units are the nodes of the network and the co-operations are indica…
A population evolution model and its applications to random networks
I. Fazekas, Cs. Noszály, A. Perecsényi
A general population evolution model is considered. Any individual of the population is characterized by its score. Certain general conditions are assumed concerning the number of…
Weights of Cliques in a Random Graph Model Based on Three-Interactions
István Fazekas, Csaba Noszály, Attila Perecsényi
A random graph evolution rule is considered. The graph evolution is based on interactions of three vertices. The weight of a clique is the number of its interactions. The asymptoti…
Strong limit theorems in the multi-color generalized allocation scheme
Alexey Chuprunov, István Fazekas
The generalized allocation scheme is studied. Its extension for coloured balls is defined. Some analogues of the Law of the Iterated Logarithm and the Strong Law of Large Numbers a…
On a General Approach to the Strong Laws of Large Numbers
István Fazekas
A general method to obtain strong laws of large numbers is studied. The method is based on abstract Hájek-Rényi type maximal inequalities. The rate of convergence in the law of lar…
The asymptotic behaviour of the weights and the degrees in an N-interactions random graph model
István Fazekas, Bettina Porvázsnyik
A random graph evolution based on the interactions of N vertices is studied. During the evolution both the preferential attachment method and the uniform choice of vertices are all…
Scale-free property for degrees and weights in an N-interactions random graph model
István Fazekas, Bettina Porvázsnyik
A general random graph evolution mechanism is defined. The evolution is a combination of the preferential attachment model and the interaction of N vertices (N>=3). A vertex in the…