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Found 8 papers, 0 papers with code
Concentration inequalities for correlated network-valued processes with applications to community estimation and changepoint analysis
Network-valued time series are currently a common form of network data.
Estimation of Number of Communities in Assortative Sparse Networks
Most community detection algorithms assume the number of communities, K, to be known a priori.
Sparse and Low-bias Estimation of High Dimensional Vector Autoregressive Models
A well-known feature of RML inference is that in general the technique produces a trade-off between sparsity and bias that depends on the choice of the regularization hyperparameter.
Hierarchical community detection by recursive partitioning
This can be done with a simple top-down recursive partitioning algorithm, starting with a single community and separating the nodes into two communities by spectral clustering repeatedly, until a stopping rule suggests there are no further communities.
Optimizing the Union of Intersections LASSO ($UoI_{LASSO}$) and Vector Autoregressive ($UoI_{VAR}$) Algorithms for Improved Statistical Estimation at Scale
The analysis of scientific data of increasing size and complexity requires statistical machine learning methods that are both interpretable and predictive.
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction
The increasing size and complexity of scientific data could dramatically enhance discovery and prediction for basic scientific applications.
Spectral Clustering and Block Models: A Review And A New Algorithm
We focus on spectral clustering of unlabeled graphs and review some results on clustering methods which achieve weak or strong consistent identification in data generated by such models.
Community Detection in Networks using Graph Distance
There are some exceptions but all have some incomplete theoretical basis.
