Abstract
Matrix completion under interval uncertainty can be cast as a matrix completion problem with element-wise box constraints. We present an efficient alternating-direction parallel coordinate-descent method for the problem. We show that the method outperforms any other known method on a benchmark in image in-painting in terms of signal-to-noise ratio, and that it provides high-quality solutions for an instance of collaborative filtering with 100,198,805 recommendations within 5 minutes on a single personal computer.
Original language | English (US) |
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Pages (from-to) | 35-43 |
Number of pages | 9 |
Journal | European Journal of Operational Research |
Volume | 256 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2017 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2016 The Authors
Keywords
- Collaborative filtering
- Coordinate descent
- Large-scale optimization
- Matrix completion
- Robust optimization
ASJC Scopus subject areas
- General Computer Science
- Modeling and Simulation
- Management Science and Operations Research
- Information Systems and Management