Subject clustering (i.e., the use of measured features to cluster subjec...
How to detect a small community in a large network is an interesting pro...
Motivated by applications in text mining and discrete distribution infer...
Real networks often have severe degree heterogeneity. We are interested ...
We collected and cleaned a large data set on publications in statistics....
The mixed-membership stochastic block model (MMSBM) is a common model fo...
SCORE was introduced as a spectral approach to network community detecti...
Lasso is a celebrated method for variable selection in linear models, bu...
The screening testing is an effective tool to control the early spread o...
As the power of FDR control methods for high-dimensional variable select...
Given a symmetric network with n nodes, how to estimate the number of
co...
The success of deep learning has inspired recent interests in applying n...
The spiked covariance model has gained increasing popularity in
high-dim...
To date, social network analysis has been largely focused on pairwise
in...
We consider the problem of decomposing a large covariance matrix into th...
Given a symmetric social network, we are interested in testing whether i...
Multivariate elliptically-contoured distributions are widely used for
mo...
SCORE is a recent approach to network community detection proposed by Ji...
State aggregation is a model reduction method rooted in control theory a...
Consider a large social network with possibly severe degree heterogeneit...
In the probabilistic topic models, the quantity of interest---a low-rank...
Consider a two-class clustering problem where we observe X_i = ℓ_i μ +
Z...