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We develop an eigenspace estimation algorithm for distributed environmentswith arbitrary node failures, where a subset of computing nodes can returnstructurally valid but otherwise arbitrarily chosen responses. Notably, thissetting encompasses several important scenarios that arise in distributedcomputing and data-collection environments such as silent/soft errors, outliersor corrupted data at certain nodes, and adversarial responses. Our estimatorbuilds upon and matches the performance of a recently proposed non-robustestimator up to an additive $\tilde{O}(\sigma \sqrt{\alpha})$ error, where$\sigma^2$ is the variance of the existing estimator and $\alpha$ is thefraction of corrupted nodes.

Communication-efficient distributed eigenspace estimation with arbitrary node failures