Advances and Open Problems in Federated Learning。Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or
whole organizations) collaboratively train a model under the orchestration of a central server (e.g. ser
This paper is about work done for result merging task of TREC 2013 Federated Web Track. We introduce three methods for calculating score of documents. These methods are based on linear combination with scores of document fields. The distinction is di
摘抄
Federated learning (aka collaborative learning) is a machine learning technique that trains an algorithm across multiple decentralized edge devices or servers holding local data samples, without exchanging their data samples.
不同于：
传统centralized ML
