Communication-Efficient Distributed Eigenspace Estimation

DOI10.1137/20M1364862zbMath1476.62198arXiv2009.02436OpenAlexW3203712890MaRDI QIDQ5162627

Vasileios Charisopoulos, Austin R. Benson, Anil Damle

Publication date: 3 November 2021

Published in: SIAM Journal on Mathematics of Data Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2009.02436

zbMATH Keywords

principal component analysisnonconvex optimizationdistributed computingspectral methodsstatistics

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Inference from stochastic processes and spectral analysis (62M15) Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) (68Q87) Numerical methods for low-rank matrix approximation; matrix compression (65F55)

Uses Software

• TensorFlow
• Wirtinger Flow

Cites Work

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• Low rank matrix recovery from rank one measurements
• The symmetric Procrustes problem
• Principal component analysis.
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• Spectral Algorithms
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• High-Dimensional Statistics
• High-Dimensional Probability
• Distributed Subgradient Methods for Multi-Agent Optimization
• The Byzantine generals problem
• Uniform Bounds for Invariant Subspace Perturbations
• Optimal Algorithms for Non-Smooth Distributed Optimization in Networks
• Communication-Efficient Distributed Statistical Inference
• Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview
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• Turning Big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering
• A dual approach for optimal algorithms in distributed optimization over networks
• Distributed Estimation for Principal Component Analysis: An Enlarged Eigenspace Analysis

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