federated learning

Empowering Farmers Through Privacy-Preserving AI: A Federated Learning Approach for Soybean Disease Classification

Learning from Unreliable Trajectories: Adversarially-Robust Federated Q-Learning

We study federated reinforcement learning in which multiple agents interact with a common Markov decision process and communicate through a central server to collaboratively learn the optimal stateaction value function. Our goal is to understand whether the sample-efficiency benefits of collaboration can be retained wh...

Operating Envelopes of Synchronous and Asynchronous Federated Learning Under Communication Impairments in Smart-Grid Sensor Networks

Federated learning (FL) for distributed smart-grid monitoring is shaped jointly by statistical heterogeneity and communication timing. This study evaluates protocol operating envelopes rather than proposing a new aggregator. A frozen confirmatory campaign compares deadline-constrained FedAvg, FedAsync, FedBuff, and Fed...

P149: Federated analytics across heterogeneous stores: Google Cloud study

Federated analytics across heterogeneous stores: Google Cloud study Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Credential: Member, IEEE (Membership # 102728576) | ORCID: 0009-0002-9180-4946 Abstract Cloud data platforms are no longer used only for rep...

Explainability and Interpretability in Medical Image Analysis

Deep learning models can achieve high performances in medical image analysis on tasks such as lesion detection (CT/MRI) and grading of tissue sections (histopathology), however, the black-box nature hinders the understanding of decision rationales to clinicians. This opacity engenders suspicion, regulatory obstacles (e...

Decentralized Learning Management Systems (DLMS)

This chapter discusses Decentralized Learning Management Systems (DLMS) as a novel method of contemporary education by combining blockchain, federated learning, and distributed technologies. It analyzes the architectural design, scalability issues, and implementation obstacles of DLMS, and stresses their benefits over...

BlockGuard: Serverless Selective Homomorphic Encryption for Federated Learning

P149: Federated analytics across heterogeneous stores: Google Cloud study

Federated analytics across heterogeneous stores: Google Cloud study Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Credential: Member, IEEE (Membership # 102728576) | ORCID: 0009-0002-9180-4946 Abstract Cloud data platforms are no longer used only for rep...

P146: Federated analytics across heterogeneous stores: Cross-cloud comparative study

Federated analytics across heterogeneous stores: Cross-cloud comparative study Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Credential: Member, IEEE (Membership # 102728576) | ORCID: 0009-0002-9180-4946 Abstract Cloud data platforms are no longer used o...

INTEGRATING ARTIFICIAL INTELLIGENCE AND BLOCKCHAIN TECHNOLOGY INTO SMART MOBILE APPLICATIONS

The rapid development of contemporary technologies tends to digitalize all services across various public and private institutions, where most services are also provided on mobile devices due to their great practical usability by people in everyday life. The integration of Blockchain Technology (BT) and Artificial Inte...

Federated Learning and Blockchain Integration for Privacy-Preserving Smart Classrooms

The development of smart classroom technology hastened the implementation of data-driven and personalized learning systems, with the significant concern of data privacy, security, and trust. In this chapter, the author introduces a combined system of Federated Learning (FL) and blockchain to implement decentralized and...

Artificial intelligence, explainable deep learning, and generative models for osteoporosis and bone disease prediction: a systematic review and future research roadmap

Osteoporosis is a major global health burden, with considerable morbidity, mortality, and healthcare costs. Artificial intelligence (AI) has opened new avenues for osteoporosis screening, bone mineral density quantification, fracture-risk prediction, and clinical decision support, but progress remains fragmented across...