Optimal change point detection and localization in sparse dynamic networks
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[1] Lizhen Lin,et al. Change-point detection in dynamic networks via graphon estimation , 2019, 1908.01823.
[2] Piotr Fryzlewicz,et al. Detecting multiple generalized change-points by isolating single ones , 2019, Metrika.
[3] George Michailidis,et al. Change Point Estimation in a Dynamic Stochastic Block Model , 2018, J. Mach. Learn. Res..
[4] A. Rinaldo,et al. Univariate mean change point detection: Penalization, CUSUM and optimality , 2018, Electronic Journal of Statistics.
[5] George Michailidis,et al. Sequential change-point detection in high-dimensional Gaussian graphical models , 2018, J. Mach. Learn. Res..
[6] Claudia Kirch,et al. A MOSUM procedure for the estimation of multiple random change points , 2018 .
[7] Kathryn Roeder,et al. Global spectral clustering in dynamic networks , 2018, Proceedings of the National Academy of Sciences.
[8] Alessandro Rinaldo,et al. Optimal Covariance Change Point Detection in High Dimension , 2017 .
[9] Jiaming Xu,et al. Rates of Convergence of Spectral Methods for Graphon Estimation , 2017, ICML.
[10] Hao Chen,et al. Asymptotic Distribution-Free Change-Point Detection for Modern Data , 2017 .
[11] Eric D. Kolaczyk,et al. Topics at the Frontier of Statistics and Network Analysis: (Re)Visiting the Foundations , 2017 .
[12] Marianna Pensky,et al. Spectral clustering in the dynamic stochastic block model , 2017, Electronic Journal of Statistics.
[13] Ivor Cribben,et al. Estimating whole‐brain dynamics by using spectral clustering , 2017 .
[14] Piotr Fryzlewicz,et al. Simultaneous multiple change-point and factor analysis for high-dimensional time series , 2016, Journal of Econometrics.
[15] Haeran Cho,et al. Change-point detection in panel data via double CUSUM statistic , 2016, 1611.08631.
[16] P. Fryzlewicz,et al. Narrowest‐over‐threshold detection of multiple change points and change‐point‐like features , 2016, Journal of the Royal Statistical Society: Series B (Statistical Methodology).
[17] Marianna Pensky,et al. Dynamic network models and graphon estimation , 2016, The Annals of Statistics.
[18] Tengyao Wang,et al. High dimensional change point estimation via sparse projection , 2016, 1606.06246.
[19] Yuguo Chen,et al. Latent Space Models for Dynamic Networks , 2015, 2005.08808.
[20] Harry Crane. Time-varying network models , 2015, 1507.07664.
[21] Vincent Miele,et al. Statistical clustering of temporal networks through a dynamic stochastic block model , 2015, 1506.07464.
[22] Piotr Fryzlewicz,et al. Multiple‐change‐point detection for high dimensional time series via sparsified binary segmentation , 2015, 1611.08639.
[23] Kevin S. Xu. Stochastic Block Transition Models for Dynamic Networks , 2014, AISTATS.
[24] Jing Lei,et al. Network Cross-Validation for Determining the Number of Communities in Network Data , 2014, 1411.1715.
[25] Piotr Fryzlewicz,et al. Wild binary segmentation for multiple change-point detection , 2014, 1411.0858.
[26] Harrison H. Zhou,et al. Rate-optimal graphon estimation , 2014, 1410.5837.
[27] Mi Zhou,et al. Sequential Change Point Detection , 2014 .
[28] Z. Wang,et al. The structure and dynamics of multilayer networks , 2014, Physics Reports.
[29] Alfred O. Hero,et al. Dynamic Stochastic Blockmodels for Time-Evolving Social Networks , 2014, IEEE Journal of Selected Topics in Signal Processing.
[30] Heng Wang,et al. Locality Statistics for Anomaly Detection in Time Series of Graphs , 2013, IEEE Transactions on Signal Processing.
[31] Po-Ling Loh,et al. Regularized M-estimators with nonconvexity: statistical and algorithmic theory for local optima , 2013, J. Mach. Learn. Res..
[32] A. Munk,et al. Multiscale change point inference , 2013, 1301.7212.
[33] S. Chatterjee,et al. Matrix estimation by Universal Singular Value Thresholding , 2012, 1212.1247.
[34] Martin J. Wainwright,et al. Communication-efficient algorithms for statistical optimization , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).
[35] L. Horváth,et al. Change‐point detection in panel data , 2012 .
[36] Z. Harchaoui,et al. Multiple Change-Point Estimation With a Total Variation Penalty , 2010 .
[37] Roman Vershynin,et al. Introduction to the non-asymptotic analysis of random matrices , 2010, Compressed Sensing.
[38] Mark E. J. Newman,et al. Stochastic blockmodels and community structure in networks , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.
[39] Laurent Massoulié,et al. Distributed user profiling via spectral methods , 2010, SIGMETRICS '10.
[40] Edoardo M. Airoldi,et al. A Survey of Statistical Network Models , 2009, Found. Trends Mach. Learn..
[41] Xiaolin Zheng,et al. Dynamic Social Network Analysis Using Latent Space Model and an Integrated Clustering Algorithm , 2009, 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing.
[42] Alexandre B. Tsybakov,et al. Introduction to Nonparametric Estimation , 2008, Springer series in statistics.
[43] Edward R. Scheinerman,et al. Random Dot Product Graph Models for Social Networks , 2007, WAW.
[44] Andrzej Rucinski,et al. Random graphs , 2006, SODA.
[45] Mark Huisman,et al. Models and Methods in Social Network Analysis: Introduction , 2005 .
[46] Yoav Seginer,et al. The Expected Norm of Random Matrices , 2000, Combinatorics, Probability and Computing.
[47] Kathryn B. Laskey,et al. Stochastic blockmodels: First steps , 1983 .
[48] Soumendu Sundar Mukherjee. On Some Inference Problems for Networks , 2018 .
[49] Alessandro Rinaldo,et al. A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening , 2017, NIPS.
[50] Moni Naor,et al. Algorithms and Models for the Web Graph , 2016, Lecture Notes in Computer Science.
[51] Le Song,et al. Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks , 2011, AISTATS.
[52] Tom A. B. Snijders,et al. Markov Chain Monte Carlo Estimation of Exponential Random Graph Models , 2002, J. Soc. Struct..
[53] CONCENTRATION OF MEASURE INEQUALITIES FOR MARKOV CHAINS AND -MIXING PROCESSES By Paul-Marie Samson , 2000 .
[54] A. Andrew,et al. Emergence of Scaling in Random Networks , 1999 .
[55] Bin Yu. Assouad, Fano, and Le Cam , 1997 .
[56] N. H. Lee,et al. Ieee Transactions on Pattern Analysis and Machine Intelligence (tpami) Attribute Fusion in a Latent Process Model for Time Series of Graphs Appendix Proofs of Some Stated Results , 2022 .