Machine learning is an integral part of high-stakes decision-making in a broad swath of human-computer interactions. You ...

As someone who has spent the better part of two decades optimizing distributed systems—from early MapReduce clusters to ...

Just as people from different countries speak different languages, AI models also create various internal "languages"—a ...

In the current era of big data, the volume of information continues to grow at an unprecedented rate, giving rise to the crucial need for efficient ...

Geo-distributed machine learning (GDML) can facilitate collaborative learning among geographically dispersed data centers to meet the demands of distributed and privacy-preserving training for ...

In this paper, we address the impact of user mobility in hierarchical federated learning (HFL) systems and propose a resource allocation and user scheduling strategy to minimize energy consumption ...