Coordinating Momenta for Cross-Silo Federated Learning

Coordinating Policy for Federated Applications

At the start of its present term of office in 1997 the UK government published a planning document promising ubiquitous access to Electronic Health Records (EHRs) held within the National Health Service (NHS). If such access is to become a reality then it is essential to guarantee confidentiality, since otherwise the media and the privacy vigilantes will prevent deployment. Among the rights inc...

Federated Meta-Learning for Recommendation

Recommender systems have been widely studied from the machine learning perspective, where it is crucial to share information among users while preserving user privacy. In this work, we present a federated meta-learning framework for recommendation in which user information is shared at the level of algorithm, instead of model or data adopted in previous approaches. In this framework, user-speci...

Federated Multi-Task Learning

Federated learning poses new statistical and systems challenges in training machinelearning models over distributed networks of devices. In this work, we show thatmulti-task learning is naturally suited to handle the statistical challenges of thissetting, and propose a novel systems-aware optimization method, MOCHA, that isrobust to practical systems issues. Our method and theor...

Federated Learning: Strategies for Improving Communication Efficiency

Federated Learning is a machine learning setting where the goal is to train a highquality centralized model with training data distributed over a large number of clients each with unreliable and relatively slow network connections. We consider learning algorithms for this setting where on each round, each client independently computes an update to the current model based on its local data, and ...

Coordinating cross-country congestion management