56 citations · 137 across the 6 of their papers we have counts for
6 papers
The Conditioning Bias in Binary Decision Trees and Random Forests and Its Elimination
Gábor Timár, György Kovács
Decision tree and random forest classification and regression are some of the most widely used in machine learning approaches. Binary decision tree implementations commonly use con…
Strongly clustered random graphs via triadic closure: An exactly solvable model
Lorenzo Cirigliano, Claudio Castellano, Gareth Baxter +1
Triadic closure, the formation of a connection between two nodes in a network sharing a common neighbor, is considered a fundamental mechanism determining the clustered nature of m…
Enhanced robustness of single-layer networks with redundant dependencies
Gábor Timár, György Kovács, José Fernando F. Mendes
Dependency links in single-layer networks offer a convenient way of modeling nonlocal percolation effects in networked systems where certain pairs of nodes are only able to functio…
Choosing among alternative histories of a tree
Gábor Timár, Rui A. da Costa, Sergey N. Dorogovtsev +1
The structure of an evolving network contains information about its past. Extracting this information efficiently, however, is, in general, a difficult challenge. We formulate a fa…
Nonbacktracking expansion of finite graphs
Gábor Timár, Rui A. da Costa, Sergey N. Dorogovtsev +1
Message passing equations yield a sharp percolation transition in finite graphs, as an artifact of the locally treelike approximation. For an arbitrary finite, connected, undirecte…
Scale-free networks with exponent one
Gábor Timár, Sergey N. Dorogovtsev, José Fernando F. Mendes
A majority of studied models for scale-free networks have degree distributions with exponents greater than . Real networks, however, can demonstrate essentially more heavy-taile…