Copertina

Guaranteed Noisy CP Tensor Recovery via Riemannian Optimization on the Segre Manifold

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xu, Ke, Han, Yuefeng
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Optimization and Control Statistics Theory Methodology 90C26 (Primary) 15A69, 62F10, 62J05, 62H25 (Secondary)
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Statistical Inference for Low-Rank Tensor Models
di: Xu, Ke, et al.
Pubblicazione: (2025)

On Testing Kronecker Product Structure in Tensor Factor Models
di: Cen, Zetai, et al.
Pubblicazione: (2025)

Identification and Estimation of Multi-order Tensor Factor Models
di: Cen, Zetai
Pubblicazione: (2025)

Unifying and Generalizing Methods for Removing Unwanted Variation Based on Negative Controls
di: Gerard, David, et al.
Pubblicazione: (2017)

A method for sparse and robust independent component analysis
di: Heinonen, Lauri, et al.
Pubblicazione: (2025)

Extreme value theory for singular subspace estimation in the matrix denoising model
di: Chang, Junhyung, et al.
Pubblicazione: (2025)

Tensor Neyman-Pearson Classification: Theory, Algorithms, and Error Control
di: Liu, Lingchong, et al.
Pubblicazione: (2025)

Tensor Factor Model Estimation by Iterative Projection
di: Han, Yuefeng, et al.
Pubblicazione: (2020)

Design-Conditional Prior Elicitation for Dirichlet Process Mixtures: A Unified Framework for Cluster Counts and Weight Control
di: Lee, JoonHo
Pubblicazione: (2026)

Variance component mixture modelling for longitudinal T-cell receptor clonal dynamics
di: Swanson, David, et al.
Pubblicazione: (2025)

Semiparametric Copula Estimation for Spatially Correlated Multivariate Mixed Outcomes: Analyzing Visual Sightings of Fin Whales from a Line Transect Survey
di: Momozaki, Tomotaka, et al.
Pubblicazione: (2023)

Simultaneous Inference for Multiple Proportions: A Multivariate Beta-Binomial Model
di: Westphal, Max
Pubblicazione: (2019)

Bayesian Analysis of Spiked Covariance Models: Correcting Eigenvalue Bias and Determining the Number of Spikes
di: Lee, Kwangmin, et al.
Pubblicazione: (2024)

Optimal designs for discrete choice models via graph Laplacians
di: Röttger, Frank, et al.
Pubblicazione: (2022)

Eigenstructure inference for high-dimensional covariance with generalized shrinkage inverse-Wishart prior
di: Kim, Seongmin, et al.
Pubblicazione: (2025)

A General Bayesian Nonparametric Approach for Estimating Population-Level and Conditional Causal Effects
di: Hur, Yongseok, et al.
Pubblicazione: (2025)

Bayesian Optimization of Noisy Log-Likelihoods Evaluated by Particle Filters -- One Parameter Case --
di: Kitagawa, Genshiro
Pubblicazione: (2026)

Flexible Bayesian Multiple Comparison Adjustment Using Dirichlet Process and Beta-Binomial Model Priors
di: Bergh, Don van den, et al.
Pubblicazione: (2022)

Some are observed, all leave traces: whole-population modeling of French elite civil servants' career paths
di: Voldoire, Théo, et al.
Pubblicazione: (2023)

Bayesian Joint Modeling of Interrater and Intrarater Reliability with Multilevel Data
di: Hawila, Nour, et al.
Pubblicazione: (2024)

Admissibility of Adaptive Monotone Step-Down Multiple Testing Procedures Under Arbitrary Covariance Dependence
di: Ghosh, Prasenjit, et al.
Pubblicazione: (2026)

Consistent DAG selection for Bayesian causal discovery under general error distributions
di: Chaudhuri, Anamitra, et al.
Pubblicazione: (2025)

Consistent Bayesian causal discovery for structural equation models with equal error variances
di: Chaudhuri, Anamitra, et al.
Pubblicazione: (2025)

Cumulant Tensors in Partitioned Independent Component Analysis
di: Garrote-López, Marina, et al.
Pubblicazione: (2024)

A new way to evaluate G-Wishart normalising constants via Fourier analysis
di: Wong, Ching, et al.
Pubblicazione: (2024)

Bi-dendrograms for clustering the categories of a multivariate categorical data set
di: Greenacre, Michael, et al.
Pubblicazione: (2025)

Sparse factor models of high dimension
di: Poignard, Benjamin, et al.
Pubblicazione: (2023)

Subspace decompositions for association structure learning in multivariate categorical response regression
di: Zhao, Hongru, et al.
Pubblicazione: (2024)

Directional testing for one-way MANOVA in divergent dimensions
di: Huang, Caizhu, et al.
Pubblicazione: (2024)

Uncertainty Quantification for Noisy Low-tubal-rank Tensor Completion
di: Shang, Jiuqian, et al.
Pubblicazione: (2026)

Symmetrisation of a class of two-sample tests by mutually considering depth ranks including functional spaces
di: Gnettner, Felix, et al.
Pubblicazione: (2023)

Simultaneous Detection and Localization of Mean and Covariance Changes in High Dimensions
di: Cui, Junfeng, et al.
Pubblicazione: (2025)

Cover It Up! Bipartite Graphs Uncover Identifiability in Sparse Factor Analysis
di: Hosszejni, Darjus, et al.
Pubblicazione: (2022)

Bernstein-von Mises Theorem for Sparse Generalized Linear Model
di: Li, Hanqing, et al.
Pubblicazione: (2026)

Improving knockoffs with conditional calibration
di: Luo, Yixiang, et al.
Pubblicazione: (2022)

Confidence and discoveries with e-values
di: Vovk, Vladimir, et al.
Pubblicazione: (2019)

Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions
di: van der Spek, Rutger, et al.
Pubblicazione: (2022)

Sparse canonical correlation analysis for multiple measurements with latent trajectories
di: Senar, Nuria, et al.
Pubblicazione: (2025)

Covariance Correction for Permutation Statistics in Multiple Testing Problems
di: Munko, Merle, et al.
Pubblicazione: (2026)

Identifying Network Hubs with the Partial Correlation Graphical LASSO
di: Bogdan, Małgorzata, et al.
Pubblicazione: (2025)