Communications of the ACM

Algorithmic Autonomy in Data-Driven AI

Data-driven AI systems increasingly influence our choices, raising concerns about autonomy, fairness, and accountability. Achieving algorithmic autonomy requires new infrastructures, motivation ...
IEEE

Implementation of Federated Learning Algorithms for Non Independent and Identically Distributed Data

Abstract: Federated Learning (FL) has emerged as a transformative approach for training machine learning models across decentralized data sources while preserving privacy. This study evaluates the ...
IEEE

Primal-Dual Fixed Point Algorithms Based on Adapted Metric for Distributed Optimization With Bounded Communication Delays

Abstract: This article concentrates on distributed optimization over networks with communication delays. Each subsystem in the network performs its local updates by using the information received from ...
IEEE

Research on System Data Security Based on State Secret Algorithm

Abstract: The need for data protection in national critical information infrastructure units has become more and more urgent with the deepening of digital transformation. At present, the rapid ...
IEEE

A Sequential and Asynchronous Federated Learning Framework for Railway Point Machine Fault Diagnosis With Imperfect Data Transmission

Abstract: Fault diagnosis of railway assets has drawn the interest of both the scholarly and engineering communities. Federated learning (FL) enables training models across distributed assets to ...