Abstract
We propose an efficient algorithm for solving group synchronization under high levels of corruption and noise, while we focus on rotation synchronization. We first describe our recent theoretically guaranteed message passing algorithm that estimates the corruption levels of themeasured group ratios. We then propose a novel reweighted least squares method to estimate the group elements, where the weights are initialized and iteratively updated using the estimated corruption levels. We demonstrate the superior performance of our algorithm over state-of-the-art methods for rotation synchronization using both synthetic and real data.
| Original language | English (US) |
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| Title of host publication | 37th International Conference on Machine Learning, ICML 2020 |
| Editors | Hal Daume, Aarti Singh |
| Publisher | International Machine Learning Society (IMLS) |
| Pages | 8755-8765 |
| Number of pages | 11 |
| ISBN (Electronic) | 9781713821120 |
| State | Published - 2020 |
| Event | 37th International Conference on Machine Learning, ICML 2020 - Virtual, Online Duration: Jul 13 2020 → Jul 18 2020 |
Publication series
| Name | 37th International Conference on Machine Learning, ICML 2020 |
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| Volume | PartF168147-12 |
Conference
| Conference | 37th International Conference on Machine Learning, ICML 2020 |
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| City | Virtual, Online |
| Period | 7/13/20 → 7/18/20 |
Bibliographical note
Funding Information:This work was supported by NSF award DMS-18-21266. We thank Tyler Maunu for his valuable comments on an earlier version of this manuscript.
Publisher Copyright:
© 2020 37th International Conference on Machine Learning, ICML 2020. All rights reserved.
