Local Algorithms for Block Models with Side Information
暂无分享,去创建一个
[1] Bruce E. Hajek,et al. Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions , 2015, IEEE Transactions on Information Theory.
[2] Anima Anandkumar,et al. A tensor approach to learning mixed membership community models , 2013, J. Mach. Learn. Res..
[3] Varun Kanade,et al. Global and Local Information in Clustering Labeled Block Models , 2014, IEEE Transactions on Information Theory.
[4] S. Kak. Information, physics, and computation , 1996 .
[5] Elchanan Mossel,et al. Consistency Thresholds for the Planted Bisection Model , 2014, STOC.
[6] Mark Jerrum,et al. The Metropolis Algorithm for Graph Bisection , 1998, Discret. Appl. Math..
[7] Bruce E. Hajek,et al. Recovering a Hidden Community Beyond the Spectral Limit in O(|E|log*|V|) Time , 2015, ArXiv.
[8] Raymond J. Mooney,et al. A probabilistic framework for semi-supervised clustering , 2004, KDD.
[9] Arindam Banerjee,et al. Semi-supervised Clustering by Seeding , 2002, ICML.
[10] Martin E. Dyer,et al. The Solution of Some Random NP-Hard Problems in Polynomial Expected Time , 1989, J. Algorithms.
[11] Anderson Y. Zhang,et al. Minimax Rates of Community Detection in Stochastic Block Models , 2015, ArXiv.
[12] T. Snijders,et al. Estimation and Prediction for Stochastic Blockmodels for Graphs with Latent Block Structure , 1997 .
[13] Florent Krzakala,et al. Comparative study for inference of hidden classes in stochastic block models , 2012, ArXiv.
[14] Andrea Montanari,et al. Tight bounds for LDPC and LDGM codes under MAP decoding , 2004, IEEE Transactions on Information Theory.
[15] XuJiaming,et al. Achieving Exact Cluster Recovery Threshold via Semidefinite Programming , 2016 .
[16] Amin Coja-Oghlan,et al. Graph Partitioning via Adaptive Spectral Techniques , 2009, Combinatorics, Probability and Computing.
[17] Frank McSherry,et al. Spectral partitioning of random graphs , 2001, Proceedings 2001 IEEE International Conference on Cluster Computing.
[18] H. Kesten,et al. Additional Limit Theorems for Indecomposable Multidimensional Galton-Watson Processes , 1966 .
[19] Afonso S. Bandeira,et al. Random Laplacian Matrices and Convex Relaxations , 2015, Found. Comput. Math..
[20] Laurent Massoulié,et al. Non-backtracking Spectrum of Random Graphs: Community Detection and Non-regular Ramanujan Graphs , 2014, 2015 IEEE 56th Annual Symposium on Foundations of Computer Science.
[21] Cristopher Moore,et al. Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.
[22] Yudong Chen,et al. Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices , 2014, J. Mach. Learn. Res..
[23] Richard M. Karp,et al. Algorithms for graph partitioning on the planted partition model , 2001, Random Struct. Algorithms.
[24] Madhu Sudan,et al. Limits of local algorithms over sparse random graphs , 2013, ITCS.
[25] Laurent Massoulié,et al. Community detection thresholds and the weak Ramanujan property , 2013, STOC.
[26] Alexandre Proutière,et al. Accurate Community Detection in the Stochastic Block Model via Spectral Algorithms , 2014, ArXiv.
[27] P. Bickel,et al. A nonparametric view of network models and Newman–Girvan and other modularities , 2009, Proceedings of the National Academy of Sciences.
[28] Fedor Nazarov,et al. Perfect matchings as IID factors on non-amenable groups , 2009, Eur. J. Comb..
[29] Anima Anandkumar,et al. A Tensor Spectral Approach to Learning Mixed Membership Community Models , 2013, COLT.
[30] Armen E. Allahverdyan,et al. Phase Transitions in Community Detection: A Solvable Toy Model , 2013, ArXiv.
[31] Elchanan Mossel,et al. Reconstruction and estimation in the planted partition model , 2012, Probability Theory and Related Fields.
[32] Alexandre Proutière,et al. Community Detection via Random and Adaptive Sampling , 2014, COLT.
[33] B. Szegedy,et al. Limits of local-global convergent graph sequences , 2012, 1205.4356.
[34] Bálint Virág,et al. Local algorithms for independent sets are half-optimal , 2014, ArXiv.
[35] Amin Coja-Oghlan,et al. A spectral heuristic for bisecting random graphs , 2005, SODA '05.
[36] Cristopher Moore,et al. Phase transitions in semisupervised clustering of sparse networks , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.
[37] Elchanan Mossel,et al. A Proof of the Block Model Threshold Conjecture , 2013, Combinatorica.
[38] Elchanan Mossel,et al. Density Evolution in the Degree-correlated Stochastic Block Model , 2015, COLT.
[39] Elchanan Mossel,et al. Belief propagation, robust reconstruction and optimal recovery of block models , 2013, COLT.
[40] Mark E. J. Newman,et al. Structure and inference in annotated networks , 2015, Nature Communications.
[41] Sujay Sanghavi,et al. Clustering Sparse Graphs , 2012, NIPS.
[42] Xiaodong Li,et al. Robust and Computationally Feasible Community Detection in the Presence of Arbitrary Outlier Nodes , 2014, ArXiv.
[43] Bernhard Schölkopf,et al. Cluster Kernels for Semi-Supervised Learning , 2002, NIPS.
[44] Alexander S. Wein,et al. A semidefinite program for unbalanced multisection in the stochastic block model , 2017, 2017 International Conference on Sampling Theory and Applications (SampTA).
[45] Bruce E. Hajek,et al. Achieving exact cluster recovery threshold via semidefinite programming , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).
[46] Emmanuel Abbe,et al. Exact Recovery in the Stochastic Block Model , 2014, IEEE Transactions on Information Theory.
[47] Roman Vershynin,et al. Community detection in sparse networks via Grothendieck’s inequality , 2014, Probability Theory and Related Fields.
[48] I. Shevtsova,et al. An improvement of the Berry–Esseen inequality with applications to Poisson and mixed Poisson random sums , 2009, 0912.2795.
[49] Emmanuel Abbe,et al. Community detection in general stochastic block models: fundamental limits and efficient recovery algorithms , 2015, ArXiv.
[50] Rüdiger L. Urbanke,et al. Modern Coding Theory , 2008 .
[51] Armen E. Allahverdyan,et al. Community detection with and without prior information , 2009, ArXiv.
[52] Chao Gao,et al. Achieving Optimal Misclassification Proportion in Stochastic Block Models , 2015, J. Mach. Learn. Res..
[53] Kathryn B. Laskey,et al. Stochastic blockmodels: First steps , 1983 .
[54] R. Karp,et al. Algorithms for graph partitioning on the planted partition model , 2001 .