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20152023
most citedLow-rank tensor completion: a Riemannian manifold preconditioning approach

82 citations · 324 across the 26 of their papers we have counts for

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5 papers · 1 filter

math.NA2017★ 1 cited

Stochastic variance reduced multiplicative update for nonnegative matrix factorization

Hiroyuki Kasai

Nonnegative matrix factorization (NMF), a dimensionality reduction and factor analysis method, is a special case in which factor matrices have low-rank nonnegative constraints. Con…

math.NA2017★ 6 cited

Fast online low-rank tensor subspace tracking by CP decomposition using recursive least squares from incomplete observations

Hiroyuki Kasai

We consider the problem of online subspace tracking of a partially observed high-dimensional data stream corrupted by noise, where we assume that the data lie in a low-dimensional…

math.NA2016★ 3 cited

A Riemannian gossip approach to decentralized matrix completion

Bamdev Mishra, Hiroyuki Kasai, Atul Saroop

In this paper, we propose novel gossip algorithms for the low-rank decentralized matrix completion problem. The proposed approach is on the Riemannian Grassmann manifold that allow…

math.NA2016★ 52 cited

Online Low-Rank Tensor Subspace Tracking from Incomplete Data by CP Decomposition using Recursive Least Squares

Hiroyuki Kasai

We propose an online tensor subspace tracking algorithm based on the CP decomposition exploiting the recursive least squares (RLS), dubbed OnLine Low-rank Subspace tracking by TEns…

math.NA2015★ 8 cited

Riemannian preconditioning for tensor completion

Hiroyuki Kasai, Bamdev Mishra

We propose a novel Riemannian preconditioning approach for the tensor completion problem with rank constraint. A Riemannian metric or inner product is proposed that exploits the le…