Frontiers

Computational Frameworks for Decision-Making: From Bayesian Inference to Reinforcement Learning Models

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...
IEEE

Federated Learning in IoT Secure and Scalable AI for Edge Devices

Abstract: Federated Learning (FL) has gained attention as a decentralized machine learning paradigm, allowing the Internet of Things (IoT) edge devices to jointly train a model without sharing local ...
Frontiers

Beyond the Algorithm: Scalable, Explainable, and Adaptive AI for High-Stakes Clinical Decision Support

Artificial Intelligence (AI) has shown strong potential in supporting clinical decision-making through Clinical Decision Support Systems (CDSSs). However, ...
IEEE

FedLOC:A Layer Output Based Compression Algorithm for Federated Learning

Abstract: Communication cost is a main challenge in Federated Learning (FL). Gradient sparsification is one of the effective ways to reduce communication data volumes by allowing clients to send only ...