Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms

Kishan Wimalawarne, Hiroshi Mamitsuka

Research output: Contribution to conferencePaperScientificpeer-review

Abstract

Coupled norms have emerged as a convex method to solve coupled tensor com-
pletion. A limitation with coupled norms is that they only induce low-rankness
using the multilinear rank of coupled tensors. In this paper, we introduce a new
set of coupled norms known as coupled nuclear norms by constraining the CP
rank of coupled tensors. We propose new coupled completion models using the
coupled nuclear norms as regularizers, which can be optimized using computa-
tionally efficient optimization methods. We derive excess risk bounds for pro-
posed coupled completion models and show that proposed norms lead to better
performance. Through simulation and real-data experiments, we demonstrate that
proposed norms achieve better performance for coupled completion compared to
existing coupled norms.
Original languageEnglish
Pages6902-6910
Number of pages9
Publication statusPublished - 2018
MoE publication typeNot Eligible
EventConference on Neural Information Processing Systems - Palais des Congrès de Montréal, Montréal, Canada
Duration: 2 Dec 20188 Dec 2018
Conference number: 32
http://nips.cc

Conference

ConferenceConference on Neural Information Processing Systems
Abbreviated titleNeurIPS
CountryCanada
CityMontréal
Period02/12/201808/12/2018
Internet address

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