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Entry-wise Matrix Completion from Noisy Entries

Sabetsarvestani, Z; Kiraly, F; Miguel, R; Rodrigues, MRD; (2018) Entry-wise Matrix Completion from Noisy Entries. In: 2018 26th European Signal Processing Conference (EUSIPCO). (pp. pp. 2603-2607). IEEE Green open access

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Abstract

We address the problem of entry-wise low-rank matrix completion in the noisy observation model. We propose a new noise robust estimator where we characterize the bias and variance of the estimator in a finite sample setting. Utilizing this estimator, we provide a new robust local matrix completion algorithm that outperforms other classic methods in reconstructing large rectangular matrices arising in a wide range of applications such as athletic performance prediction and recommender systems. The simulation results on synthetic and real data show that our algorithm outperforms other state-of-the-art and baseline algorithms in matrix completion in reconstructing rectangular matrices.

Type: Proceedings paper
Title: Entry-wise Matrix Completion from Noisy Entries
Event: 26th European Signal Processing Conference (EUSIPCO), 3-7 September 2018, Roma, Italy
ISBN-13: 978-9-0827-9701-5
Open access status: An open access version is available from UCL Discovery
DOI: 10.23919/EUSIPCO.2018.8553561
Publisher version: https://doi.org/10.23919/EUSIPCO.2018.8553561
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Matrices , Noise measurement , Prediction algorithms , Signal processing algorithms , Estimation , Europe , Signal processing
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/10063310
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