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Clustering is an underspecified task: there are no universal criteria for what makes a good clustering. This is especially true for relational data, where similarity can be based on the features of individuals, the relationships between…

Machine Learning · Statistics 2017-09-29 Sebastijan Dumancic , Hendrik Blockeel

Network or graph structures are ubiquitous in the study of complex systems. Often, we are interested in complexity trends of these system as it evolves under some dynamic. An example might be looking at the complexity of a food web as…

Information Theory · Computer Science 2012-01-23 Russell K. Standish

The concepts of symmetry and its breakdown are investigated in two different terms according to whether the resulting asymmetry is universal or only obtained for a special configuration: we shall illustrate this by considering in the first…

General Physics · Physics 2022-03-23 Luca Fabbri

We investigate the role of a statistical complexity measure to assign equilibration in isolated quantum systems. While unitary dynamics preserve global purity, expectation values of observables often exhibit equilibration-like behavior,…

Quantum Physics · Physics 2025-08-14 Marcos G. Alpino , Tiago Debarba , Reinaldo O. Vianna , André T. Cesário

The non-trivial structure of such complex systems makes the analysis of their collective behavior a challenge. The problem is even more difficult when the information is distributed across networks (e.g., communication networks in different…

Social and Information Networks · Computer Science 2018-02-08 Carlo Spatocco , Giovanni Stilo , Carlotta Domeniconi , Alessandro D'Andrea

Unveil the homophilic/heterophilic behaviors that characterize the wiring patterns of complex networks is an important task in social network analysis, often approached studying the assortative mixing of node attributes. Recent works…

Social and Information Networks · Computer Science 2020-12-10 Giulio Rossetti , Salvatore Citraro , Letizia Milli

Sample weighting is widely used in deep learning. A large number of weighting methods essentially utilize the learning difficulty of training samples to calculate their weights. In this study, this scheme is called difficulty-based…

Machine Learning · Computer Science 2023-01-13 Xiaoling Zhou , Ou Wu , Weiyao Zhu , Ziyang Liang

Interpreting experimental data in high school experiments can be a difficult task for students, especially when there is large variation in the data. At the same time, calculating the standard deviation poses a challenge for students. In…

Physics Education · Physics 2022-10-18 Karel Kok , Burkhard Priemer

This paper addresses the issues of conservativeness and computational complexity of probabilistic robustness analysis. We solve both issues by defining a new sampling strategy and robustness measure. The new measure is shown to be much less…

Applications · Statistics 2008-05-12 Xinjia Chen , Kemin Zhou , Jorge L. Aravena

We propose a complexity measure which addresses the functional flexibility of networks. It is conjectured that the functional flexibility is reflected in the topological diversity of the assigned graphs, resulting from a resolution of their…

Condensed Matter · Physics 2009-11-10 Hildegard Meyer-Ortmanns

A new notion of typicality for arbitrary probability measures on standard Borel spaces is proposed, which encompasses the classical notions of weak and strong typicality as special cases. Useful lemmas about strong typical sets, including…

Information Theory · Computer Science 2016-11-17 Junekey Jeon

Assembly theory (AT) quantifies selection using the assembly equation and identifies complex objects that occur in abundance based on two measurements, assembly index and copy number, where the assembly index is the minimum number of…

Network or graph structures are ubiquitous in the study of complex systems. Often, we are interested in complexity trends of these system as it evolves under some dynamic. An example might be looking at the complexity of a food web as…

Information Theory · Computer Science 2007-07-16 Russell K. Standish

Introduced the quantitative measure of the structural complexity of the graph (complex network, etc.) based on a procedure similar to the renormalization process, considering the difference between actual and averaged graph structures on…

Physics and Society · Physics 2024-06-05 A. A. Snarskii

Given a graph with node attributes, what neighborhoods are anomalous? To answer this question, one needs a quality score that utilizes both structure and attributes. Popular existing measures either quantify the structure only and ignore…

Social and Information Networks · Computer Science 2016-01-26 Bryan Perozzi , Leman Akoglu

A good deal of current research in complex networks involves the characterization and/or classification of the topological properties of given structures, which has motivated several respective measurements. This letter proposes a framework…

Physics and Society · Physics 2016-07-26 Cesar H. Comin , Filipi N. Silva , Luciano da F. Costa

We introduce a new measure of coarseness for characterizing phase separation processes such as those described by Cahn--Hilliard equations. An advantage of our measure is that it remains consistent throughout the evolution, including for…

Analysis of PDEs · Mathematics 2026-01-22 Peter Howard , Adam Larios , Quyuan Lin

Structural quantities such as order parameters and correlation functions are often employed to gain insight into the physical behavior and properties of condensed matter systems. While standard quantities for characterizing structure exist,…

Soft Condensed Matter · Physics 2017-08-23 Aaron S. Keys , Christopher R. Iacovella , Sharon C. Glotzer

A geometric mechanism that may, in analogy to similar notions in physics, be considered as "symmetry breaking" in geometry is described, and several instances of this mechanism in differential geometry are discussed: it is shown how…

Differential Geometry · Mathematics 2022-06-28 Andreas Fuchs , Udo Hertrich-Jeromin , Mason Pember

This paper introduces a comprehensive framework for complex-valued probability measures and explores their novel applications in information theory and statistical analysis. We define a complex probability measure as a phase-modulated…

Information Theory · Computer Science 2026-03-16 Siang Cheng , Hejun Xu , Tianxiao Pang