IEEE

HFed-CMS: Cluster-Based Hierarchical Federated Multi-Task Learning with Fair Edge Node Selection

Abstract: Hierarchical Federated Learning (HFL) has emerged as a promising paradigm for distributed machine learning in edge computing environments. By introducing intermediate edge servers between ...
IEEE

SCALE: Tackling Communication Bottlenecks in Confidential Distributed Machine Learning

Abstract: Machine Learning (ML) has become a cornerstone in numerous applications, creating the need for secure and efficient distributed ML frameworks. However, maintaining data privacy in these ...
Communications of the ACMOpinion

From Distributed Intelligence to Verifiable Responsibility

Artificial intelligence (AI) is no longer confined to centralized data centers. It is increasingly distributed across edge ...

Introducing the Agentic Marketing Mastermind for Agency Owners

Elevate Your Marketing Game with the Agentic Marketing Mastermind New York, United States - March 17, 2026 / Search ...
marktechpost

A Coding Guide to Build a Scalable End-to-End Analytics and Machine Learning Pipeline on Millions of Rows Using Vaex

In this tutorial, we design an end-to-end, production-style analytics and modeling pipeline using Vaex to operate efficiently on millions of rows without materializing data in memory. We generate a ...