federated learning

Federated Label Verification: Reproducibility Code and Experimental Results

This software and reproducibility package supports the study “Label-Induced Bias and Verification-Cost Trade-offs in Federated Learning: A Budget-Constrained Crowd-Intelligence Approach.” It contains source code, configuration information, analysis scripts, and final five-seed experimental outputs for federated learnin...

Machine Learning Medical Image Classification and Detection Data Analysis

Medical imaging is a core component of healthcare in the contemporary era, but the sheer scale of digital image data requires effective automated processing. Machine learning methods have become effective tools for classification and detection, both in classic procedures using traditional machine learning models and in...

Foundation of Digital Medical Imaging Technologies

Digital medical imaging has developed as an indispensable modality in the context of modern health care systems, allowing for non-invasive visualization of internal anatomic and physiologic structures to successfully facilitate right diagnosis, treatment planning, and monitoring. In the context of the rapid development...

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...