7 citations · 7 across the 5 of their papers we have counts for
5 papers
FedVG: Gradient-Guided Aggregation for Enhanced Federated Learning
Alina Devkota, Jacob Thrasher, Donald Adjeroh +2
Federated Learning (FL) enables collaborative model training across multiple clients without sharing their private data. However, data heterogeneity across clients leads to client…
Local K-Similarity Constraint for Federated Learning with Label Noise
Sanskar Amgain, Prashant Shrestha, Bidur Khanal +5
Federated learning on clients with noisy labels is a challenging problem, as such clients can infiltrate the global model, impacting the overall generalizability of the system. Exi…
Federated Foundation Model for GI Endoscopy Images
Alina Devkota, Annahita Amireskandari, Joel Palko +5
Gastrointestinal (GI) endoscopy is essential in identifying GI tract abnormalities in order to detect diseases in their early stages and improve patient outcomes. Although deep lea…
TE-SSL: Time and Event-aware Self Supervised Learning for Alzheimer's Disease Progression Analysis
Jacob Thrasher, Alina Devkota, Ahmed Tafti +2
Alzheimer's Dementia (AD) represents one of the most pressing challenges in the field of neurodegenerative disorders, with its progression analysis being crucial for understanding…
Multimodal Federated Learning in Healthcare: a Review
Jacob Thrasher, Alina Devkota, Prasiddha Siwakotai +5
Recent advancements in multimodal machine learning have empowered the development of accurate and robust AI systems in the medical domain, especially within centralized database sy…