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pro vyhledávání: '"Newman, M. E."'
Mutual information is commonly used as a measure of similarity between competing labelings of a given set of objects, for example to quantify performance in classification and community detection tasks. As argued recently, however, the mutual informa
Externí odkaz:
http://arxiv.org/abs/2405.05393
Autor:
Jerdee, Maximilian, Newman, M. E. J.
Patterns of wins and losses in pairwise contests, such as occur in sports and games, consumer research and paired comparison studies, and human and animal social hierarchies, are commonly analyzed using probabilistic models that allow one to quantify
Externí odkaz:
http://arxiv.org/abs/2312.04711
Normalized mutual information is widely used as a similarity measure for evaluating the performance of clustering and classification algorithms. In this paper, we argue that results returned by the normalized mutual information are biased for two rea
Externí odkaz:
http://arxiv.org/abs/2307.01282
Autor:
Polanco, Austin, Newman, M. E. J.
Publikováno v:
Phys. Rev. E 108, 024311 (2023)
We study core-periphery structure in networks using inference methods based on a flexible network model that allows for traditional onion-like cores within cores, but also for hierarchical tree-like structures and more general non-nested types of str
Externí odkaz:
http://arxiv.org/abs/2301.03630
Autor:
Newman, M. E. J.
Publikováno v:
Proc. R. Soc. London A 479, 20220774 (2023)
Networks and network computations have become a primary mathematical tool for analyzing the structure of many kinds of complex systems, ranging from the Internet and transportation networks to biochemical interactions and social networks. A common ta
Externí odkaz:
http://arxiv.org/abs/2211.05054
Publikováno v:
Proc. R. Soc. London A 480, 20230470 (2024)
The number of non-negative integer matrices with given row and column sums appears in a variety of problems in mathematics and statistics but no closed-form expression for it is known, so we rely on approximations of various kinds. Here we describe a
Externí odkaz:
http://arxiv.org/abs/2209.14869
Autor:
Fortunato, Santo, Newman, M. E. J.
Publikováno v:
Nature Physics 18, 848-850 (2022)
A fundamental technical challenge in the analysis of network data is the automated discovery of communities - groups of nodes that are strongly connected or that share similar features or roles. In this commentary we review progress in the field over
Externí odkaz:
http://arxiv.org/abs/2208.00111
Autor:
Newman, M. E. J.
Publikováno v:
Journal of Machine Learning Research 24, 238 (2023)
We study the ranking of individuals, teams, or objects, based on pairwise comparisons between them, using the Bradley-Terry model. Estimates of rankings within this model are commonly made using a simple iterative algorithm first introduced by Zermel
Externí odkaz:
http://arxiv.org/abs/2207.00076