Statistical mechanics of low-rank tensor decomposition

DOI10.1088/1742-5468/AB3216zbMath1459.82212arXiv1810.10065OpenAlexW2949575763MaRDI QIDQ5854119

Jonathan Kadmon, Surya Ganguli

Publication date: 16 March 2021

Published in: Journal of Statistical Mechanics: Theory and Experiment (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1810.10065

Mathematics Subject Classification ID

Bayesian inference (62F15) Dynamic and nonequilibrium phase transitions (general) in statistical mechanics (82C26) Statistical aspects of big data and data science (62R07)

Related Items (3)

Analyticity of the energy in an Ising spin glass with correlated disorder ⋮ Hamilton-Jacobi equations for inference of matrix tensor products ⋮ Hamilton-Jacobi equations for nonsymmetric matrix inference

Cites Work

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• Tensor Decompositions and Applications
• Analysis of individual differences in multidimensional scaling via an \(n\)-way generalization of ``Eckart-Young decomposition
• Tensor decompositions for learning latent variable models
• Statistical mechanics of complex neural systems and high dimensional data
• Constrained low-rank matrix estimation: phase transitions, approximate message passing and applications
• Information, Physics, and Computation
• Tensor Decomposition for Signal Processing and Machine Learning
• Statistical Physics of Spin Glasses and Information Processing
• The Dynamics of Message Passing on Dense Graphs, with Applications to Compressed Sensing
• Algorithmic Learning Theory
• Statistical theory of superlattices

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