Statistical limits of sparse mixture detection
From MaRDI portal
Publication:2084466
DOI10.1214/22-EJS2053MaRDI QIDQ2084466
Publication date: 18 October 2022
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2104.02507
Nonparametric hypothesis testing (62G10) Bayesian problems; characterization of Bayes procedures (62C10) Large deviations (60F10)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Innovated higher criticism for detecting sparse signals in correlated noise
- Higher criticism for large-scale inference, especially for rare and weak effects
- Minimax rates of community detection in stochastic block models
- The sparse Poisson means model
- Microarrays, empirical Bayes and the two-groups model
- Large deviations techniques and applications.
- Some problems of hypothesis testing leading to infinitely divisible distributions
- Phase transitions for high dimensional clustering and related problems
- Higher criticism for detecting sparse heterogeneous mixtures.
- Minimax rates in network analysis: graphon estimation, community detection and hypothesis testing
- Testing equivalence of clustering
- Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences
- Unsupervised empirical Bayesian multiple testing with external covariates
- Signal detection via Phi-divergences for general mixtures
- Hypothesis testing for high-dimensional sparse binary regression
- High-dimensional Ising model selection with Bayesian information criteria
- Optimality of Graphlet Screening in High Dimensional Variable Selection
- Optimal Detection of Sparse Mixtures Against a Given Null Distribution
- Impossibility of successful classification when useful features are rare and weak
- Optimal Detection of Heterogeneous and Heteroscedastic Mixtures
- Multiple Testing with the Structure-Adaptive Benjamini–Hochberg Algorithm
- Rare and weak effects in large-scale inference: methods and phase diagrams
- Information, Physics, and Computation
- Community Detection and Stochastic Block Models
- AdaPT: An Interactive Procedure for Multiple Testing with Side Information
- Lower bounds for testing graphical models: colorings and antiferromagnetic Ising models
- Concentration of Maxima and Fundamental Limits in High-Dimensional Testing and Inference
- Covariate Powered Cross-Weighted Multiple Testing
- Testing Bayesian Networks
- Information-Theoretic Limits of Selecting Binary Graphical Models in High Dimensions
- Convex Analysis