The resistance perturbation distance: A metric for the analysis of dynamic networks

Monnig, Nathan D.; Meyer, François G.

doi:10.1016/j.dam.2017.10.007

Title: The resistance perturbation distance: A metric for the analysis of dynamic networks

Authors:

Monnig, Nathan D.;

Publication Date:: Thu Feb 01 00:00:00 EST 2018

Sponsoring Org.:: USDOE

OSTI Identifier:: 1845924

Alternate Identifier(s):: OSTI ID: 1549112

Grant/Contract Number:: FC02–03ER25574; B600360; DMS 0941476; DMS 1407340

Resource Type:: Published Article

Journal Name:: Discrete Applied Mathematics

Additional Journal Information:: Journal Name: Discrete Applied Mathematics Journal Volume: 236 Journal Issue: C; Journal ID: ISSN 0166-218X

Publisher:: Elsevier

Country of Publication:: Netherlands

Language:: English

Citation Formats


                    Monnig, Nathan D., and Meyer, François G. The resistance perturbation distance: A metric for the analysis of dynamic networks.  Netherlands: N. p., 2018. 
Web.  doi:10.1016/j.dam.2017.10.007.

Copy to clipboard


                    Monnig, Nathan D., & Meyer, François G. The resistance perturbation distance: A metric for the analysis of dynamic networks.  Netherlands.  https://doi.org/10.1016/j.dam.2017.10.007

Copy to clipboard


                    Monnig, Nathan D., and Meyer, François G. Thu .  
"The resistance perturbation distance: A metric for the analysis of dynamic networks".  Netherlands.  https://doi.org/10.1016/j.dam.2017.10.007.

Copy to clipboard


                    
@article{osti_1845924,

  title        = {The resistance perturbation distance: A metric for the analysis of dynamic networks},

  author       = {Monnig, Nathan D. and Meyer, François G.},

  abstractNote = {},

  doi          = {10.1016/j.dam.2017.10.007},

  journal      = {Discrete Applied Mathematics},

  number       = C,

  volume       = 236,

  place        = {Netherlands},

  year         = {Thu Feb 01 00:00:00 EST 2018},

  month        = {Thu Feb 01 00:00:00 EST 2018}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Publisher's Version of Record
https://doi.org/10.1016/j.dam.2017.10.007

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 11 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Works referenced in this record:

Graph based anomaly detection and description: a survey
journal, July 2014

Akoglu, Leman; Tong, Hanghang; Koutra, Danai
Data Mining and Knowledge Discovery, Vol. 29, Issue 3
DOI: 10.1007/s10618-014-0365-y

Reality mining: sensing complex social systems
journal, November 2005

Eagle, Nathan; (Sandy) Pentland, Alex
Personal and Ubiquitous Computing, Vol. 10, Issue 4
DOI: 10.1007/s00779-005-0046-3

First-passage properties of the Erdos–Renyi random graph
journal, December 2004

Sood, V.; Redner, S.; ben-Avraham, D.
Journal of Physics A: Mathematical and General, Vol. 38, Issue 1
DOI: 10.1088/0305-4470/38/1/007

Spectral sparsification of graphs: theory and algorithms
journal, August 2013

Batson, Joshua; Spielman, Daniel A.; Srivastava, Nikhil
Communications of the ACM, Vol. 56, Issue 8
DOI: 10.1145/2492007.2492029

Graph Kernels from the Jensen-Shannon Divergence
journal, September 2012

Bai, Lu; Hancock, Edwin R.
Journal of Mathematical Imaging and Vision, Vol. 47, Issue 1-2
DOI: 10.1007/s10851-012-0383-6

Graph isomorphism in quasipolynomial time [extended abstract]
conference, January 2016

Babai, László
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing - STOC 2016
DOI: 10.1145/2897518.2897542

On hitting times for a simple random walk on dense Erdös–Rényi random graphs
journal, June 2014

Löwe, Matthias; Torres, Felipe
Statistics & Probability Letters, Vol. 89
DOI: 10.1016/j.spl.2014.02.017

The electrical resistance of a graph captures its commute and cover times
journal, December 1996

Chandra, Ashok K.; Raghavan, Prabhakar; Ruzzo, Walter L.
Computational Complexity, Vol. 6, Issue 4
DOI: 10.1007/BF01270385

Improving robustness of complex networks via the effective graph resistance
journal, September 2014

Wang, Xiangrong; Pournaras, Evangelos; Kooij, Robert E.
The European Physical Journal B, Vol. 87, Issue 9
DOI: 10.1140/epjb/e2014-50276-0

Practical graph isomorphism, II
journal, January 2014

McKay, Brendan D.; Piperno, Adolfo
Journal of Symbolic Computation, Vol. 60
DOI: 10.1016/j.jsc.2013.09.003

Minimizing Effective Resistance of a Graph
journal, January 2008

Ghosh, Arpita; Boyd, Stephen; Saberi, Amin
SIAM Review, Vol. 50, Issue 1
DOI: 10.1137/050645452

Anomaly detection in dynamic networks: a survey
journal, March 2015

Ranshous, Stephen; Shen, Shitian; Koutra, Danai
Wiley Interdisciplinary Reviews: Computational Statistics, Vol. 7, Issue 3
DOI: 10.1002/wics.1347

Graph similarity and distance in graphs
journal, February 1998

Chartrand, G.; Kubicki, G.; Schultz, M.
Aequationes Mathematicae, Vol. 55, Issue 1-2
DOI: 10.1007/s000100050025

Epidemic processes in complex networks
journal, August 2015

Pastor-Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet
Reviews of Modern Physics, Vol. 87, Issue 3
DOI: 10.1103/RevModPhys.87.925

Efficient Graphlet Counting for Large Networks
conference, November 2015

Ahmed, Nesreen K.; Neville, Jennifer; Rossi, Ryan A.
2015 IEEE International Conference on Data Mining (ICDM)
DOI: 10.1109/ICDM.2015.141

Networks and epidemic models
journal, May 2005

Keeling, Matt J.; Eames, Ken T. D.
Journal of The Royal Society Interface, Vol. 2, Issue 4
DOI: 10.1098/rsif.2005.0051

Web graph similarity for anomaly detection
journal, February 2010

Papadimitriou, Panagiotis; Dasdan, Ali; Garcia-Molina, Hector
Journal of Internet Services and Applications, Vol. 1, Issue 1
DOI: 10.1007/s13174-010-0003-x

Graph Matching and Learning in Pattern Recognition in the last 10 Years
journal, February 2014

Foggia, Pasquale; Percannella, Gennaro; Vento, Mario
International Journal of Pattern Recognition and Artificial Intelligence, Vol. 28, Issue 01
DOI: 10.1142/S0218001414500013

Combinatorial preconditioners and multilevel solvers for problems in computer vision and image processing
journal, December 2011

Koutis, Ioannis; Miller, Gary L.; Tolliver, David
Computer Vision and Image Understanding, Vol. 115, Issue 12
DOI: 10.1016/j.cviu.2011.05.013

Effective graph resistance
journal, November 2011

Ellens, W.; Spieksma, F. M.; Van Mieghem, P.
Linear Algebra and its Applications, Vol. 435, Issue 10
DOI: 10.1016/j.laa.2011.02.024

Quick Approximation to Matrices and Applications
journal, February 1999

Frieze, Alan; Kannan, Ravi
Combinatorica, Vol. 19, Issue 2
DOI: 10.1007/s004930050052

Lean Algebraic Multigrid (LAMG): Fast Graph Laplacian Linear Solver
journal, January 2012

Livne, Oren E.; Brandt, Achi
SIAM Journal on Scientific Computing, Vol. 34, Issue 4
DOI: 10.1137/110843563

Graph sparsification by effective resistances
conference, May 2008

Spielman, Daniel A.; Srivastava, Nikhil
STOC '08: Symposium on Theory of Computing, Proceedings of the fortieth annual ACM symposium on Theory of computing
DOI: 10.1145/1374376.1374456

Spectral Sparsification of Graphs
journal, January 2011

Spielman, Daniel A.; Teng, Shang-Hua
SIAM Journal on Computing, Vol. 40, Issue 4
DOI: 10.1137/08074489X

Recent advances in graph-based pattern recognition with applications in document analysis
journal, May 2011

Bunke, Horst; Riesen, Kaspar
Pattern Recognition, Vol. 44, Issue 5
DOI: 10.1016/j.patcog.2010.11.015

A study of graph spectra for comparing graphs and trees
journal, September 2008

Wilson, Richard C.; Zhu, Ping
Pattern Recognition, Vol. 41, Issue 9
DOI: 10.1016/j.patcog.2008.03.011

Similar Records in DOE PAGES and OSTI.GOV collections:

The resistance perturbation distance: A metric for the analysis of dynamic networks

Journal Article Monnig, Nathan D. ; Meyer, François G. - Discrete Applied Mathematics

Not provided.
https://doi.org/10.1016/j.dam.2017.10.007
Enhancing Least-Squares Finite Element Methods Through a Quantity-of-Interest

Journal Article Chaudhry, Jehanzeb Hameed ; Cyr, Eric C. ; Liu, Kuo ; ... - SIAM Journal on Numerical Analysis

Here, we introduce an approach that augments least-squares finite element formulations with user-specified quantities-of-interest. The method incorporates the quantity-of-interest into the least-squares functional and inherits the global approximation properties of the standard formulation as well as increased resolution of the quantity-of-interest. We establish theoretical properties such as optimality and enhanced convergence under a set of general assumptions. Central to the approach is that it offers an element-level estimate of the error in the quantity-of-interest. As a result, we introduce an adaptive approach that yields efficient, adaptively refined approximations. Several numerical experiments for a range of situations are presented to supportmore »« less
https://doi.org/10.1137/13090496X

Full Text Available
Persistent Homology Metrics Reveal Quantum Fluctuations and Reactive Atoms in Path Integral Dynamics

Journal Article Hu, Yunfeng ; Ounkham, Phonemany ; Marsalek, Ondrej ; ... - Frontiers in Chemistry

Nuclear quantum effects (NQEs) are known to impact a number of features associated with chemical reactivity and physicochemical properties, particularly for light atoms and at low temperatures. In the imaginary time path integral formalism, each atom is mapped onto a “ring polymer” whose spread is related to the quantum mechanical uncertainty in the particle’s position, i.e., its thermal wavelength. A number of metrics have previously been used to investigate and characterize this spread and explain effects arising from quantum delocalization, zero-point energy, and tunneling. Many of these shape metrics consider just the instantaneous structure of the ring polymers. However, givenmore »« less
https://doi.org/10.3389/fchem.2021.624937
Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to human mitochondrial DNA restriction data

Journal Article Excoffier, L ; Smouse, P E ; Quattro, J M

The authors present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes. This analysis of molecular variance (AMOVA) produces estimates of variance components and F-statistic analogs, designated here as [Phi]-statistics, reflecting the correlation of haplotypic diversity at different levels of hierarchical subdivision. The method is flexible enough to accommodate several alternative input matrices, corresponding to different types of molecular data, as well as different types of evolutionary assumptions, without modifying the basicmore »« less
Using cross-layer adaptations for dynamic data management in large scale coupled scientific workflows, In: SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis

Conference Jin, Tong ; Zhang, Fan ; Sun, Qian ; ... - 2013 INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS (SC)

As system scales and application complexity grow, managing and processing simulation data has become a significant challenge. While recent approaches based on data staging and in-situ/in-transit data processing are promising, dynamic data volumes and distributions, such as those occurring in AMR-based simulations, make the efficient use of these techniques challenging. In this paper we propose cross-layer adaptations that address these challenges and respond at runtime to dynamic data management requirements. Specifically we explore (1) adaptations of the spatial resolution at which the data is processed, (2) dynamic placement and scheduling of data processing kernels, and (3) dynamic allocation of in-transitmore »« less
https://doi.org/10.1145/2503210.2503301

Similar Records

Title: The resistance perturbation distance: A metric for the analysis of dynamic networks

Citation Formats

Graph based anomaly detection and description: a survey journal, July 2014

Reality mining: sensing complex social systems journal, November 2005

First-passage properties of the Erdos–Renyi random graph journal, December 2004

Spectral sparsification of graphs: theory and algorithms journal, August 2013

Graph Kernels from the Jensen-Shannon Divergence journal, September 2012

Graph isomorphism in quasipolynomial time [extended abstract] conference, January 2016

On hitting times for a simple random walk on dense Erdös–Rényi random graphs journal, June 2014

The electrical resistance of a graph captures its commute and cover times journal, December 1996

Improving robustness of complex networks via the effective graph resistance journal, September 2014

Practical graph isomorphism, II journal, January 2014

Minimizing Effective Resistance of a Graph journal, January 2008

Anomaly detection in dynamic networks: a survey journal, March 2015

Graph similarity and distance in graphs journal, February 1998

Epidemic processes in complex networks journal, August 2015

Efficient Graphlet Counting for Large Networks conference, November 2015

Networks and epidemic models journal, May 2005

Web graph similarity for anomaly detection journal, February 2010

Graph Matching and Learning in Pattern Recognition in the last 10 Years journal, February 2014

Combinatorial preconditioners and multilevel solvers for problems in computer vision and image processing journal, December 2011

Effective graph resistance journal, November 2011

Quick Approximation to Matrices and Applications journal, February 1999

Lean Algebraic Multigrid (LAMG): Fast Graph Laplacian Linear Solver journal, January 2012

Graph sparsification by effective resistances conference, May 2008

Spectral Sparsification of Graphs journal, January 2011

Recent advances in graph-based pattern recognition with applications in document analysis journal, May 2011

A study of graph spectra for comparing graphs and trees journal, September 2008

Graph based anomaly detection and description: a survey
journal, July 2014

Reality mining: sensing complex social systems
journal, November 2005

First-passage properties of the Erdos–Renyi random graph
journal, December 2004

Spectral sparsification of graphs: theory and algorithms
journal, August 2013

Graph Kernels from the Jensen-Shannon Divergence
journal, September 2012

Graph isomorphism in quasipolynomial time [extended abstract]
conference, January 2016

On hitting times for a simple random walk on dense Erdös–Rényi random graphs
journal, June 2014

The electrical resistance of a graph captures its commute and cover times
journal, December 1996

Improving robustness of complex networks via the effective graph resistance
journal, September 2014

Practical graph isomorphism, II
journal, January 2014

Minimizing Effective Resistance of a Graph
journal, January 2008

Anomaly detection in dynamic networks: a survey
journal, March 2015

Graph similarity and distance in graphs
journal, February 1998

Epidemic processes in complex networks
journal, August 2015

Efficient Graphlet Counting for Large Networks
conference, November 2015

Networks and epidemic models
journal, May 2005

Web graph similarity for anomaly detection
journal, February 2010

Graph Matching and Learning in Pattern Recognition in the last 10 Years
journal, February 2014

Combinatorial preconditioners and multilevel solvers for problems in computer vision and image processing
journal, December 2011

Effective graph resistance
journal, November 2011

Quick Approximation to Matrices and Applications
journal, February 1999

Lean Algebraic Multigrid (LAMG): Fast Graph Laplacian Linear Solver
journal, January 2012

Graph sparsification by effective resistances
conference, May 2008

Spectral Sparsification of Graphs
journal, January 2011

Recent advances in graph-based pattern recognition with applications in document analysis
journal, May 2011

A study of graph spectra for comparing graphs and trees
journal, September 2008