Copertina

Data-Driven optimal shrinkage of singular values under high-dimensional noise with separable covariance structure with application

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Su, Pei-Chun, Wu, Hau-Tieng
Natura:	Preprint
Pubblicazione:	2022
Soggetti:	Applications
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Data-driven time-frequency tessellation for signals with oscillatory amplitude envelopes and instantaneous frequency, with application to photoplethysmograhy
di: Laine, Jennifer, et al.
Pubblicazione: (2026)

Design a Metric Robust to Complicated High Dimensional Noise for Efficient Manifold Denoising
di: Wu, Hau-Tieng
Pubblicazione: (2024)

Sparse covariate-driven factorization of high-dimensional brain connectivity with application to site effect correction
di: Zhang, Rongqian, et al.
Pubblicazione: (2026)

Asymptotic non-linear shrinkage and eigenvector overlap for weighted sample covariance
di: Oriol, Benoit
Pubblicazione: (2024)

Uncertainty quantification of synchrosqueezing transform under complicated nonstationary noise
di: Wu, Hau-Tieng, et al.
Pubblicazione: (2025)

Simultaneous test of the mean vectors and covariance matrices for high-dimensional data using RMT
di: Niu, Zhenzhen, et al.
Pubblicazione: (2024)

Doubly regularized generalized linear models for spatial observations with high-dimensional covariates
di: Sondhi, Arjun, et al.
Pubblicazione: (2024)

Unsupervised Ensembling of Multiple Software Sensors with Phase Synchronization: A Robust Approach For Electrocardiogram-derived Respiration
di: McErlean, Jacob, et al.
Pubblicazione: (2020)

Anisotropic local law for non-separable sample covariance matrices
di: Fan, Zhou, et al.
Pubblicazione: (2026)

Multi-objective Bayesian optimization for blocking in extreme value analysis and its application in additive manufacturing
di: Irfan, Shehzaib, et al.
Pubblicazione: (2025)

Bayesian high-dimensional biological pathway-guided mediation analysis with application to metabolomics
di: Zhang, Yuzi, et al.
Pubblicazione: (2025)

Feature aware covariance estimation, with application to mixtures of chemical exposures
di: Bersson, Elizabeth, et al.
Pubblicazione: (2025)

Rank-based transfer learning for high-dimensional survival data with application to sepsis data
di: Qiao, Nan, et al.
Pubblicazione: (2025)

On the Consistency of Bayesian Adaptive Testing under the Rasch Model
di: Yang, Hau-Hung, et al.
Pubblicazione: (2024)

Tail-adaptive Bayesian shrinkage
di: Lee, Se Yoon, et al.
Pubblicazione: (2020)

Rank-adaptive covariance testing with applications to genomics and neuroimaging
di: Veitch, David, et al.
Pubblicazione: (2023)

CSTEapp: An interactive R-Shiny application of the covariate-specific treatment effect curve for visualizing individualized treatment rule
di: Zhou, Yi, et al.
Pubblicazione: (2025)

Forecasting high-dimensional functional time series with dual-factor structures
di: Tang, Chen, et al.
Pubblicazione: (2021)

Adaptive L-tests for high dimensional independence
di: Zhao, Ping, et al.
Pubblicazione: (2026)

A scalable Bayesian double machine learning framework for high dimensional causal estimation, with application to racial disproportionality assessment
di: Luo, Yu, et al.
Pubblicazione: (2025)

Model-based bi-clustering using multivariate Poisson-lognormal with general block-diagonal covariance matrix and its applications
di: Kral, Caitlin, et al.
Pubblicazione: (2025)

Learning non-Gaussian spatial distributions via Bayesian transport maps with parametric shrinkage
di: Chakraborty, Anirban, et al.
Pubblicazione: (2024)

Introducing shrinkage in heavy-tailed state space models to predict equity excess returns
di: Huber, Florian, et al.
Pubblicazione: (2018)

Benchmarking covariate-adjustment strategies for randomized clinical trials
di: Shao, Yulin, et al.
Pubblicazione: (2026)

Factorized Binary Search: change point detection in the network structure of multivariate high-dimensional time series
di: Ondrus, Martin, et al.
Pubblicazione: (2021)

Mixture-of-experts Wishart model for covariance matrices with an application to Cancer drug screening
di: Mai, The Tien, et al.
Pubblicazione: (2026)

Adaptive active subspace-based metamodeling for high-dimensional reliability analysis
di: Kim, Jungho, et al.
Pubblicazione: (2023)

E-TRIALS: Empowering Data-Driven Decisions to Enhance Computer-Based Learning Platforms
di: Siedahmed, Abubakir, et al.
Pubblicazione: (2025)

Direct covariance matrix estimation with compositional data
di: Molstad, Aaron J., et al.
Pubblicazione: (2022)

Profile least squares estimation in networks with covariates
di: Chandna, Swati, et al.
Pubblicazione: (2024)

Corporate Financial Distress Prediction: Based on Multi-source Data and Feature Selection
di: Ding, Yi, et al.
Pubblicazione: (2024)

Circula-based multivariate distributions on the flat torus, with applications in structural biology
di: Carrière, Guillaume, et al.
Pubblicazione: (2026)

Area between trajectories: Insights into optimal group selection and trajectory heterogeneity in group-based trajectory modeling
di: Hsiao, Yi-Chen, et al.
Pubblicazione: (2025)

Study and application on the optimal quantile forecast of precipitation in an ensemble forecast system
di: Lianglyu Chen, et al.
Pubblicazione: (2024)

Test for high-dimensional linear hypothesis of mean vectors via random integration
di: Li, Jianghao, et al.
Pubblicazione: (2024)

Research on adaptive particle swarm optimization particle filter target tracking algorithm in wireless sensor networks
di: Chun‐Yan Jiang, et al.
Pubblicazione: (2024)

Hybrid methods for missing categorical covariates in Cox model
di: Dioni, Abdoulaye, et al.
Pubblicazione: (2025)

Errors-in-variables regression for dependent data with estimated error covariance matrix: To prewhiten or not?
di: Qiu, Jingkun, et al.
Pubblicazione: (2026)

Bayesian material flow analysis for systems with multiple levels of disaggregation and high dimensional data
di: Wang, Junyang, et al.
Pubblicazione: (2022)

Utilising high-dimensional data in randomised clinical trials: a review of methods and practice
di: Cherlin, Svetlana, et al.
Pubblicazione: (2023)