Keyphrases
Adjacency Spectral Embedding
100%
Health Expenditure
100%
Two-sample
100%
Connectome
100%
Nonparametric
75%
US Adults
66%
Maximum Mean Discrepancy
60%
Sub-Gaussian
58%
Vertex Nomination
50%
Expectation-solution Algorithm
50%
Graph Correlation
50%
Tensor Perturbations
50%
Latent Structure
50%
Brain Networks
50%
Optimal Transport
50%
Hypothesis Testing
50%
Latent Position
50%
Low-rank Matrix
50%
Singular Vectors
50%
Number of Vertices
50%
Sparse Principal Component Analysis
50%
Procrustes
50%
Iterative Algorithm
50%
Structured Networks
50%
Perturbation Bound
50%
Analysis Application
50%
Tensor SVD
50%
Cluster Analysis
50%
Clustering Methods
50%
Estimation Method
50%
Mixed Membership
50%
Comorbidity
50%
Heteroscedasticity
50%
Community Membership
50%
High-order Orthogonal Iteration
50%
Spectral Graph Partitioning
50%
Sub-Gaussian Noise
50%
Recovery Guarantee
50%
Block Model
50%
Multiscale Graph
50%
High-order
50%
Consistent Estimation
50%
Semi-supervised Regression
50%
Signal-to-noise Ratio
41%
Spectral Properties
41%
Leave-one-out
41%
Random Dot Product Graph
35%
Drosophila Brain
35%
Two-graph
35%
Berry-Esseen Theorem
33%
Mathematics
Gaussian Distribution
60%
Random Graph
53%
Cluster Analysis
50%
Matrix (Mathematics)
50%
Clustering Method
50%
Singular Vector
50%
Hypothesis Test
50%
Regularization
50%
Stochastics
50%
Optimal Transport
50%
Gaussian Mixture Model
50%
Powerful Test
50%
Principal Component Analysis
50%
Tensor
50%
Wide Range
41%
Dot Product
41%
Graph Model
41%
Probability Theory
33%
Optimality
25%
Disjoint Subset
25%
Expectation-Maximization Algorithm
25%
Statistical Hypothesis Testing
25%
Maximum Likelihood
25%
Concludes
25%
Limiting Distribution
25%
Generating Distribution
20%
Spectral Property
20%
Noise Ratio
20%
Random Noise
20%
Covariate
16%
Inner Product
16%
Graph Embedding
16%
Regression Model
16%
Edge
16%
Sub-Field
16%
Applied Statistics
16%
Perturbation Theory
16%
Frobenius Norm
16%
Simulation Study
10%
Additive Noise
10%
Exchangeability
10%
Mixture Model
10%
Dimensional Space
10%
Asymptotic Distribution
10%
Covariance Structure
10%
Social Network Analysis
10%
Magnetic Resonance Imaging
10%
Mixed Tensor
10%
Identifiability
10%
Error Bound
10%
Computer Science
Simulated Data
75%
Component Analysis
50%
Synthetic Data
50%
Regularization Method
50%
Principal Components
50%
Cluster Profile
50%
Cluster Formation
50%
Regularization
50%
Clustering Algorithm
50%
Unsupervised Clustering
50%
Community Membership
50%
Gaussian White Noise
50%
Cluster Analysis
50%
Clustering Method
50%
Estimation Procedure
50%
Clustering Graph
50%
Gaussian Mixture Model
33%
Health Care
33%
Gaussian Mixture
33%
Simplex
25%
Convex Combination
25%
Supplementary Material
25%
Order Structure
25%
Spectral Property
25%
Estimation Accuracy
25%
Noise-to-Signal Ratio
25%
Learning System
25%
Machine Learning
25%
Care Utilization
16%
Limiting Distribution
16%
Principal Eigenvector
16%
Estimation Error
16%
maximum-likelihood
16%
Full Advantage
16%
Likelihood Estimation
16%
Private Individual
16%
Disjoint Subset
16%
Longitudinal Data
16%
