Recommender system is an essential component of web services to engage users. Popular
recommender systems model user preferences and item properties using a large amount of …

To enable large-scale machine learning in bandwidth-hungry environments such as
wireless networks, significant progress has been made recently in designing communication …

Federated learning (FL) that enables edge devices to collaboratively learn a shared model
while keeping their training data locally has received great attention recently and can protect …

To address the big data challenges, serverless multi-party collaborative training has recently
attracted attention in the data mining community, since they can cut down the …

Decentralized Federated Learning (DeFL) plays a critical role in improving effectiveness of
training and has been proved to give great scope to the development of edge computing …

Differential private optimization for nonconvex smooth objective is considered. In the
previous work, the best known utility bound is $\widetilde O (\sqrt {d}/(n\varepsilon_\mathrm …

Collaborative learning has received huge interests due to its capability of exploiting the
collective computing power of the wireless edge devices. However, during the learning …

Federated learning (FL) is a prevailing distributed learning paradigm, where a large number
of workers jointly learn a model without sharing their training data. However, high …

In recent years, privacy-preserving machine learning algorithms have attracted increasing
attention because of their important applications in many scientific fields. However, in the …

The interest in federated learning has surged in recent research due to its unique ability to
train a global model using privacy-secured information held locally on each client. This …