Smoothed analysis of tensor decompositions

DOI10.1145/2591796.2591881zbMath1315.68203arXiv1311.3651OpenAlexW2057214765MaRDI QIDQ5259595

Aditya Bhaskara, Ankur Moitra, Aravindan Vijayaraghavan, Moses Charikar

Publication date: 26 June 2015

Published in: Proceedings of the forty-sixth annual ACM symposium on Theory of computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1311.3651

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Multilinear algebra, tensor calculus (15A69)

Related Items

Smoothed analysis for tensor methods in unsupervised learning, On the optimization landscape of tensor decompositions, Overcomplete Order-3 Tensor Decomposition, Blind Deconvolution, and Gaussian Mixture Models, Unnamed Item, Unnamed Item, Effective Criteria for Specific Identifiability of Tensors and Forms, Complete decomposition of symmetric tensors in linear time and polylogarithmic precision, Speeding up random walk mixing by starting from a uniform vertex, Absolute reconstruction for sums of powers of linear forms: degree 3 and beyond, Concentration inequalities for random tensors, Composition-aware spectroscopic tomography, Recovering Structured Probability Matrices, Universality of the least singular value for the sum of random matrices, Homotopy techniques for tensor decomposition and perfect identifiability, An operator theoretic approach to nonparametric mixture models, Unnamed Item, Polynomial Learning of Distribution Families, Provable ICA with unknown Gaussian noise, and implications for Gaussian mixtures and autoencoders

Uses Software

• SuLQ

Cites Work

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