Message Passing Least Squares Framework and its Application to Rotation Synchronization

Yunpeng Shi, Gilad Lerman
Proceedings of the 37th International Conference on Machine Learning, PMLR 119:8796-8806, 2020.

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 the measured 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.

Cite this Paper

BibTeX
@InProceedings{pmlr-v119-shi20b, title = {Message Passing Least Squares Framework and its Application to Rotation Synchronization}, author = {Shi, Yunpeng and Lerman, Gilad}, booktitle = {Proceedings of the 37th International Conference on Machine Learning}, pages = {8796--8806}, year = {2020}, editor = {III, Hal Daumé and Singh, Aarti}, volume = {119}, series = {Proceedings of Machine Learning Research}, month = {13--18 Jul}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v119/shi20b/shi20b.pdf}, url = {https://proceedings.mlr.press/v119/shi20b.html}, 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 the measured 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.} }
Endnote
%0 Conference Paper %T Message Passing Least Squares Framework and its Application to Rotation Synchronization %A Yunpeng Shi %A Gilad Lerman %B Proceedings of the 37th International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2020 %E Hal Daumé III %E Aarti Singh %F pmlr-v119-shi20b %I PMLR %P 8796--8806 %U https://proceedings.mlr.press/v119/shi20b.html %V 119 %X 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 the measured 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.
APA
Shi, Y. & Lerman, G.. (2020). Message Passing Least Squares Framework and its Application to Rotation Synchronization. Proceedings of the 37th International Conference on Machine Learning, in Proceedings of Machine Learning Research 119:8796-8806 Available from https://proceedings.mlr.press/v119/shi20b.html.

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