ArticleElectronic journal of statistics2026
Distributed robust estimation and inference with contaminated data.
Article in Electronic journal of statistics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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3 authors.
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Abstract
We study the problem of robust estimation and inference for contaminated data in distributed learning systems. Existing methods, such as those designed for Byzantine failures, typically assume that contamination is limited to a small subset of machines experiencing complete failure. In contrast, we address
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