Noisy Tensor Completion for Tensors with a Sparse Canonical Polyadic Factor
Machine Learning
2017-04-11 v1
Abstract
In this paper we study the problem of noisy tensor completion for tensors that admit a canonical polyadic or CANDECOMP/PARAFAC (CP) decomposition with one of the factors being sparse. We present general theoretical error bounds for an estimate obtained by using a complexity-regularized maximum likelihood principle and then instantiate these bounds for the case of additive white Gaussian noise. We also provide an ADMM-type algorithm for solving the complexity-regularized maximum likelihood problem and validate the theoretical finding via experiments on synthetic data set.
Keywords
Cite
@article{arxiv.1704.02534,
title = {Noisy Tensor Completion for Tensors with a Sparse Canonical Polyadic Factor},
author = {Swayambhoo Jain and Alexander Gutierrez and Jarvis Haupt},
journal= {arXiv preprint arXiv:1704.02534},
year = {2017}
}