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We study a sparse negative binomial regression (NBR) for count data by showing the non-asymptotic advantages of using the elastic-net estimator. Two types of oracle inequalities are derived for the NBR's elastic-net estimates by using the…

Machine Learning · Statistics 2022-01-11 Huiming Zhang , Jinzhu Jia

In this work, water distribution systems are regarded as large sparse planar graphs with complex network characteristics and the relationship between important topological features of the network (i.e. structural robustness and loop…

Physics and Society · Physics 2010-09-23 A. Yazdani , P. Jeffrey

Modelling systems with networks has been a powerful approach to tame the complexity of several phenomena. Unfortunately, such an approach is often made difficult by the large number of variables to take into consideration. Methods of…

Physics and Society · Physics 2023-10-17 Gianmarco Ricciardi , Guido Montagna , Guido Caldarelli , Giulio Cimini

Prestrained elastic networks arise in a number of biological and technological systems ranging from the cytoskeleton of cells to tensegrity structures. To understand the response of such a network as a function of the prestrain, we consider…

Statistical Mechanics · Physics 2022-07-13 Ihusan Adam , Franco Bagnoli , Duccio Fanelli , L. Mahadevan , Paolo Paoletti

We explore the possibilities of using energy minimization for the numerical modeling of strain localization in solids as a sharp discontinuity in the displacement field. For this purpose, we consider (regularized) strong discontinuity…

Machine Learning · Computer Science 2025-01-14 Omar León , Víctor Rivera , Angel Vázquez-Patiño , Jacinto Ulloa , Esteban Samaniego

Power grid outages cause huge economical and societal costs. Disruptions in the power distribution grid are responsible for a significant fraction of electric power unavailability to customers. The impact of extreme weather conditions,…

Systems and Control · Computer Science 2015-06-30 Yakup Koc , Abhishek Raman , Martijn Warnier , Tarun Kumar

We present a general and flexible procedure which allows for the reduction (or expansion) of any dynamical network while preserving the spectrum of the network's adjacency matrix. Computationally, this process is simple and easily…

Dynamical Systems · Mathematics 2010-10-21 L. A. Bunimovich , B. Z. Webb

Networks of elastic fibers are ubiquitous in biological systems and often provide mechanical stability to cells and tissues. Fiber reinforced materials are also common in technology. An important characteristic of such materials is their…

By performing extensive simulations with unprecedentedly large system sizes, we unveil how rigidity influences the fracture of disordered materials. We observe the largest damage in networks with connectivity close to the isostatic point…

Soft Condensed Matter · Physics 2020-01-15 Simone Dussi , Justin Tauber , Jasper van der Gucht

Effectively preserving both the structural and dynamical properties during the reduction of complex networks remains a significant research topic. Existing network reduction methods based on renormalization group or sampling often face…

Social and Information Networks · Computer Science 2025-07-15 Dan Chen , Housheng Su , Yong Wang , Jie Liu

We propose a protocol to model accurately the electromechanical behavior of dielectric elastomer membranes using experimental data of stress-stretch and voltage-stretch tests. We show how the relationship between electric displacement and…

Soft Condensed Matter · Physics 2018-11-14 Giuseppe Zurlo , Michel Destrade , Tongqing Lu

We propose a dissipative electro-elastic network model (DENM) to describe the dynamics and statistics of electrostatic fluctuations at active sites of proteins. The model combines the harmonic network of residue beads with overdamped…

Biological Physics · Physics 2015-06-03 Daniel R. Martin , S. Banu Ozkan , Dmitry V. Matyushov

Finding a set of nodes in a network, whose removal fragments the network below some target size at minimal cost is called network dismantling problem and it belongs to the NP-hard computational class. In this paper, we explore the…

Social and Information Networks · Computer Science 2019-09-20 Xiao-Long Ren , Nino Antulov-Fantulin

Network robustness is a measure a network's ability to survive adversarial attacks. But not all parts of a network are equal. K-cores, which are dense subgraphs, are known to capture some of the key properties of many real-life networks.…

Social and Information Networks · Computer Science 2020-12-21 Palash Dey , Suman Kalyan Maity , Sourav Medya , Arlei Silva

Multiple polymer networks, such as double-network elastomers comprising a sacrificial and a matrix network, exhibit exceptional mechanical resilience, commonly attributed to the formation of an extended damage zone before a crack can grow.…

Kron reduction is used to simplify the analysis of multi-machine power systems under certain steady state assumptions that underly the usage of phasors. In this paper we show how to perform Kron reduction for a class of electrical networks…

Systems and Control · Computer Science 2013-04-03 Sina Y. Caliskan , Paulo Tabuada

It has recently been discovered that the conclusions of many highly influential econometrics studies can be overturned by removing a very small fraction of their samples (often less than $0.5\%$). These conclusions are typically based on…

Machine Learning · Computer Science 2024-10-11 Ittai Rubinstein , Samuel B. Hopkins

Just as a herd of animals relies on its robust social structure to survive in the wild, similarly robustness is a crucial characteristic for the survival of a complex network under attack. The capacity to measure robustness in complex…

Networking and Internet Architecture · Computer Science 2008-11-27 Ali Sydney , Caterina Scoglio , Phillip Schumm , Robert Kooij

The traditional approach to network robustness, is based on comparing network parameters before and after an event of nodes removal, such as the change in network diameter, the change in giant component size and the existence of giant…

Physics and Society · Physics 2018-12-27 Amikam Patron , Reuven Cohen

Spatial heterogeneity in the elastic properties of soft random solids is investigated via a two-pronged approach. First, a nonlocal phenomenological model for the elastic free energy is examined. This features a quenched random kernel,…

Disordered Systems and Neural Networks · Physics 2011-12-06 Xiaoming Mao , Paul M. Goldbart , Xiangjun Xing , Annette Zippelius