Showing stat.MLShow all
2 papers · 1 filter
stat.ML2021
Linear Regression with Distributed Learning: A Generalization Error Perspective
Martin Hellkvist, Ayça Özçelikkale, Anders Ahlén
Distributed learning provides an attractive framework for scaling the learning task by sharing the computational load over multiple nodes in a network. Here, we investigate the per…
stat.ML2020
Generalization Error for Linear Regression under Distributed Learning
Martin Hellkvist, Ayça Özçelikkale, Anders Ahlén
Distributed learning facilitates the scaling-up of data processing by distributing the computational burden over several nodes. Despite the vast interest in distributed learning, g…