Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications
about
Efficient discovery of overlapping communities in massive networksHierarchical Block Structures and High-Resolution Model Selection in Large NetworksEfficient Monte Carlo and greedy heuristic for the inference of stochastic block modelsInfinite-degree-corrected stochastic block modelScalable detection of statistically significant communities and hierarchies, using message passing for modularityCross-validation estimate of the number of clusters in a networkCompleteness of Community Structure in NetworksInference on graphs via semidefinite programmingPhase transitions in semidefinite relaxations.Spectral redemption in clustering sparse networks.Block models and personalized PageRankClassifying patents based on their semantic content.Nonparametric Bayesian inference of the microcanonical stochastic block model.Structural inference for uncertain networks.Inferring the mesoscale structure of layered, edge-valued, and time-varying networks.Multiple phases in modularity-based community detection.Model selection for degree-corrected block models.Message-passing approach for recurrent-state epidemic models on networks.Universal phase transition in community detectability under a stochastic block model.Identification of core-periphery structure in networks.Finding communities in sparse networks.Social significance of community structure: statistical view.Finite-size analysis of the detectability limit of the stochastic block model.Resolution of ranking hierarchies in directed networks.Spectral partitioning in equitable graphs.Exotic phase transitions of k-cores in clustered networks.Detectability thresholds of general modular graphs.Phase transitions in semisupervised clustering of sparse networks.Community detection in networks with unequal groups.Nonbacktracking operator for the Ising model and its applications in systems with multiple states.Message-passing approach for threshold models of behavior in networks.How modular structure can simplify tasks on networks: parameterizing graph optimization by fast local community detection.General optimization technique for high-quality community detection in complex networks.Improving the performance of algorithms to find communities in networks.Stochastic fluctuations and the detectability limit of network communities.Parsimonious module inference in large networks.Statistical test for detecting community structure in real-valued edge-weighted graphs.Generalized Communities in Networks.Detectability Thresholds and Optimal Algorithms for Community Structure in Dynamic NetworksHigh Modularity Creates Scaling Laws.
P2860
Q24626714-8D11F31F-A724-4F65-A107-72930C6CB7D5Q27336408-36DB724D-507C-4BBB-AD4E-1FB7F51601A3Q27445228-95CEA549-33FC-4E43-BB2D-DB93F477A229Q28423154-66685A82-00D4-4993-A282-3B4BC0AD2777Q30612188-76881C8D-8B93-4C12-88F8-B97DD8B54B96Q33789979-924C9D68-13C7-49A6-A22A-31A56ED36351Q33902825-EC2F2BE4-DCA1-4FCC-8EAB-12FB3413D011Q36831429-732578A5-33ED-455E-8D61-2591DECBDCDFQ36831458-8425D1D1-50DC-44D7-9262-A7D40EA70FFDQ37421201-6B3CD749-434A-4151-9182-6F483EB1E51AQ37577256-5806E1A6-B3A9-4187-9401-5D74270548C3Q38377508-AFFA7041-1EAA-4562-AD3F-DC24A2DA7B21Q38957023-8BB10FB8-A579-4CE1-98F7-9F4BA674E125Q40002037-EF7146D9-DAA3-4FDC-89BB-B126FAEB4B18Q40324965-F2DAAA0B-3538-4042-9541-8BFAE43362B5Q40324978-C4374A55-0EE5-4DBD-9594-E6D8A43DE273Q40745547-E05DE200-63AB-450E-B36F-0C756EA39B10Q40993504-D981720A-50E9-44D6-9896-BB558EA2ADD1Q41076946-756A2F85-5C08-4E60-AFB2-8FBF6E630CBCQ41076952-D12B598B-6E18-442A-AF0C-C4238FD1A2D6Q41821118-3EC4A7F9-398A-464A-BA32-63D07BE7DB9EQ46912353-1E0A83CF-678B-49EF-878D-8D20ACEE21B6Q47200174-AF794B4A-2EC9-4A16-ADA0-0835887A7A94Q47549583-C76DCB52-AF5C-443C-BE80-AA8F7394DA15Q47765593-EF663234-B686-4600-87E7-423EC7F2E5A7Q47969210-B5752BB6-8939-462C-A06E-77B33FD75453Q47969560-6BC04E27-300D-4636-A47B-1DA9117B940FQ50616321-6A33E522-7202-4007-8F93-4AF11E586052Q50714158-E86E55EB-1875-488A-AC0F-0B1EB42B3E9BQ50914672-08318963-3E08-4809-90C1-6BDEAAC8B66CQ51019223-94F5AC6D-54AA-4920-9E2A-E505477AF4ABQ51027839-60D6F4E7-1971-4D3D-85A2-65AA566D20F6Q51056661-0EA78DA6-E3CF-44AF-9FB2-2BB4962B972FQ51094228-59F1DF2E-FF88-44D1-8F37-BE5DCE94AFF0Q51117503-6324A32B-40C2-4E62-B47D-3E5034CC410DQ51237025-6DFB11FA-8C41-4547-9734-90902FCF6C17Q52646660-92F1E4D2-A84A-4A38-8402-EC1FA1625A9CQ53550379-7DF4BB48-C144-41F2-8820-B98EE7490E40Q54241866-9A778604-5534-4C27-A917-ECADFC9173D9Q55428164-1109D21E-0F63-4E23-8712-0C85E297FAC6
P2860
Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications
description
2011 nî lūn-bûn
@nan
2011 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի դեկտեմբերին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Asymptotic analysis of the sto ...... d its algorithmic applications
@ast
Asymptotic analysis of the sto ...... d its algorithmic applications
@en
Asymptotic analysis of the sto ...... d its algorithmic applications
@nl
type
label
Asymptotic analysis of the sto ...... d its algorithmic applications
@ast
Asymptotic analysis of the sto ...... d its algorithmic applications
@en
Asymptotic analysis of the sto ...... d its algorithmic applications
@nl
prefLabel
Asymptotic analysis of the sto ...... d its algorithmic applications
@ast
Asymptotic analysis of the sto ...... d its algorithmic applications
@en
Asymptotic analysis of the sto ...... d its algorithmic applications
@nl
P2860
P1433
P1476
Asymptotic analysis of the sto ...... d its algorithmic applications
@en
P2093
Cristopher Moore
Lenka Zdeborová
P2860
P304
P356
10.1103/PHYSREVE.84.066106
P407
P433
P577
2011-12-12T00:00:00Z