Pages that link to "Item:Q90065"

The following pages link to Likelihood-based model selection for stochastic block models (Q90065):

Displaying 50 items.

• Model selection for Gaussian latent block clustering with the integrated classification likelihood (Q75065) (← links)
• Estimating the number of communities by spectral methods (Q90067) (← links)
• Adjusted chi-square test for degree-corrected block models (Q90068) (← links)
• nett (Q90069) (← links)
• Network Cross-Validation for Determining the Number of Communities in Network Data (Q159626) (← links)
• (Q159628) (redirect page) (← links)
• randnet (Q159656) (← links)
• Large-scale estimation of random graph models with local dependence (Q830532) (← links)
• Inference for a generalised stochastic block model with unknown number of blocks and non-conjugate edge models (Q830563) (← links)
• Community detection by \(L_{0}\)-penalized graph Laplacian (Q1639201) (← links)
• Weighted stochastic block model (Q2066716) (← links)
• Optimal adaptivity of signed-polygon statistics for network testing (Q2073714) (← links)
• Modeling the social media relationships of Irish politicians using a generalized latent space stochastic blockmodel (Q2078310) (← links)
• Extended stochastic block models with application to criminal networks (Q2080752) (← links)
• Overlapping community detection in networks via sparse spectral decomposition (Q2121698) (← links)
• The Bethe Hessian and information theoretic approaches for online change-point detection in network data (Q2121711) (← links)
• Scalable estimation of epidemic thresholds via node sampling (Q2121712) (← links)
• A likelihood-ratio type test for stochastic block models with bounded degrees (Q2123258) (← links)
• Hybrid maximum likelihood inference for stochastic block models (Q2129593) (← links)
• Edgeworth expansions for network moments (Q2131253) (← links)
• Asymptotically efficient estimators for stochastic blockmodels: the naive MLE, the rank-constrained MLE, and the spectral estimator (Q2137006) (← links)
• On equivalence of likelihood maximization of stochastic block model and constrained nonnegative matrix factorization (Q2149274) (← links)
• Consistency and asymptotic normality of stochastic block models estimators from sampled data (Q2209826) (← links)
• Maximum likelihood estimation of sparse networks with missing observations (Q2242863) (← links)
• Vertex nomination: the canonical sampling and the extended spectral nomination schemes (Q2305315) (← links)
• Test on stochastic block model: local smoothing and extreme value theory (Q2674944) (← links)
• Fast learning algorithm for stochastic block model (Q2984839) (← links)
• The highest dimensional stochastic blockmodel with a regularized estimator (Q3195174) (← links)
• (Q4998971) (← links)
• On model selection for dense stochastic block models (Q5066878) (← links)
• Network Structure Change Point Detection by Posterior Predictive Discrepancy (Q5117924) (← links)
• Corrected Bayesian Information Criterion for Stochastic Block Models (Q5146029) (← links)
• Probabilistic Community Detection With Unknown Number of Communities (Q5231515) (← links)
• (Q5376720) (← links)
• Hierarchical Community Detection by Recursive Partitioning (Q5885119) (← links)
• Estimation and selection for the latent block model on categorical data (Q5963820) (← links)
• Using Maximum Entry-Wise Deviation to Test the Goodness of Fit for Stochastic Block Models (Q6040696) (← links)
• Subsampling spectral clustering for stochastic block models in large-scale networks (Q6071693) (← links)
• Mixture models and networks: The stochastic blockmodel (Q6078169) (← links)
• Consistent Estimation of the Number of Communities via Regularized Network Embedding (Q6079724) (← links)
• Power enhancement and phase transitions for global testing of the mixed membership stochastic block model (Q6103213) (← links)
• Universal rank inference via residual subsampling with application to large networks (Q6136584) (← links)
• A survey on model-based co-clustering: high dimension and estimation challenges (Q6138123) (← links)
• Reliable prediction in the Markov stochastic block model (Q6175910) (← links)
• Statistical embedding: beyond principal components (Q6181742) (← links)
• Efficient split likelihood-based method for community detection of large-scale networks (Q6541758) (← links)
• Consistent estimation of the number of communities in stochastic block models using cross-validation (Q6543836) (← links)
• Community detection with nodal information: likelihood and its variational approximation (Q6543838) (← links)
• Statistical inference on group Rasch mixture network models (Q6543851) (← links)
• Fallacy of data-selective inference in modelling networks (Q6543962) (← links)