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arXiv · 2206.04713

A Resilient Distributed Boosting Algorithm

Yuval Filmus·Idan Mehalel·Shay Moran
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Abstract

Given a learning task where the data is distributed among several parties, communication is one of the fundamental resources which the parties would like to minimize. We present a distributed boosting algorithm which is resilient to a limited amount of noise. Our algorithm is similar to classical boosting algorithms, although it is equipped with a new component, inspired by Impagliazzo's hard-core lemma [Impagliazzo95], adding a robustness quality to the algorithm. We also complement this result by showing that resilience to any asymptotically larger noise is not achievable by a communication-efficient algorithm.

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Yuval Filmus, Idan Mehalel, Shay Moran. 2022-06-09. A Resilient Distributed Boosting Algorithm. https://arxiv.org/abs/2206.04713

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