论文标题
弹性分布式增强算法
A Resilient Distributed Boosting Algorithm
论文作者
论文摘要
考虑到数据在几个方之间分配的学习任务，沟通是当事方希望最小化的基本资源之一。我们提出了分布式增强算法，该算法具有有限噪声的弹性。我们的算法类似于经典的增强算法，尽管它配备了一种新组件，灵感来自Impagliazzo的硬核引理[Impagliazzo95]，为算法增添了稳健的质量。我们还通过表明对任何渐近上更大的噪声的韧性是无法通过沟通效率算法来实现的，从而补充了这一结果。
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.
