An optimal statistical and computational framework for generalized tensor estimation
From MaRDI portal
Publication:2119217
DOI10.1214/21-AOS2061zbMath1486.62161arXiv2002.11255OpenAlexW3007235251MaRDI QIDQ2119217
Rebecca Willett, Anru R. Zhang, Rungang Han
Publication date: 23 March 2022
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2002.11255
nonconvex optimizationimage denoisinggradient descentminimax optimalitylow-rank tensorgeneralize tensor estimation
Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Minimax procedures in statistical decision theory (62C20) Nonconvex programming, global optimization (90C26) Multilinear algebra, tensor calculus (15A69)
Related Items (5)
Inference for low-rank tensors -- no need to debias ⋮ Generalized Low-Rank Plus Sparse Tensor Estimation by Fast Riemannian Optimization ⋮ High-dimensional low-rank tensor autoregressive time series modeling ⋮ Long random matrices and tensor unfolding ⋮ Low-rank matrix estimation via nonconvex optimization methods in multi-response errors-in-variables regression
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Tensor Decompositions and Applications
- On tensor completion via nuclear norm minimization
- Optimal rates of convergence for noisy sparse phase retrieval via thresholded Wirtinger flow
- Tensor decompositions and sparse log-linear models
- Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion
- Spectral clustering in the dynamic stochastic block model
- Multilinear tensor regression for longitudinal relational data
- Cross: efficient low-rank tensor completion
- Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm
- Multilayer tensor factorization with applications to recommender systems
- Debiasing the Lasso: optimal sample size for Gaussian designs
- On polynomial time methods for exact low-rank tensor completion
- Feature selection for data integration with mixed multiview data
- Statistical limits of spiked tensor models
- Poisson noise reduction with non-local PCA
- Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach
- Three-way clustering of multi-tissue multi-individual gene expression data using semi-nonnegative tensor decomposition
- Generalized high-dimensional trace regression via nuclear norm regularization
- Phase transition in the spiked random tensor with Rademacher prior
- Low rank tensor recovery via iterative hard thresholding
- Convex regularization for high-dimensional multiresponse tensor regression
- Exact matrix completion via convex optimization
- Statistically optimal and computationally efficient low rank tensor completion from noisy entries
- Dynamical Approximation by Hierarchical Tucker and Tensor-Train Tensors
- Tensor decompositions for learning latent variable models
- Minimax Optimal Rates for Poisson Inverse Problems With Physical Constraints
- Simultaneously Structured Models With Application to Sparse and Low-Rank Matrices
- Phase Retrieval via Wirtinger Flow: Theory and Algorithms
- Blind Deconvolution Using Convex Programming
- Tensor completion and low-n-rank tensor recovery via convex optimization
- Constrained low-rank matrix estimation: phase transitions, approximate message passing and applications
- Tensor Completion in Hierarchical Tensor Representations
- Multiscale Poisson Intensity and Density Estimation
- A Multilinear Singular Value Decomposition
- On the Best Rank-1 and Rank-(R1 ,R2 ,. . .,RN) Approximation of Higher-Order Tensors
- Tensor SVD: Statistical and Computational Limits
- Nuclear norm of higher-order tensors
- Poisson Matrix Recovery and Completion
- Robust Multilinear Tensor Rank Estimation Using Higher Order Singular Value Decomposition and Information Criteria
- Multiscale modeling and estimation of Poisson processes with application to photon-limited imaging
- On Tensors, Sparsity, and Nonnegative Factorizations
- Spectral Algorithms for Tensor Completion
- ISLET: Fast and Optimal Low-Rank Tensor Regression via Importance Sketching
- A Deterministic Theory for Exact Non-Convex Phase Retrieval
- Sparse and Low-Rank Tensor Estimation via Cubic Sketchings
- Optimal Sparse Singular Value Decomposition for High-Dimensional High-Order Data
- Generalized Canonical Polyadic Tensor Decomposition
- Consistent community detection in multi-layer network data
- Multisample estimation of bacterial composition matrices in metagenomics data
- Learning High-Dimensional Generalized Linear Autoregressive Models
- Finding Low-Rank Solutions via Nonconvex Matrix Factorization, Efficiently and Provably
- Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview
- On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank One Perturbations of Gaussian Tensors
- Tight Oracle Inequalities for Low-Rank Matrix Recovery From a Minimal Number of Noisy Random Measurements
- Tensor Regression with Applications in Neuroimaging Data Analysis
- Latent Space Models for Dynamic Networks
- Tensor Learning for Regression
- Most Tensor Problems Are NP-Hard
- Applied Multiway Data Analysis
- Provable Sparse Tensor Decomposition
This page was built for publication: An optimal statistical and computational framework for generalized tensor estimation
