14 citations · 32 across the 6 of their papers we have counts for
4 papers · 1 filter
Predicting Survival of Hemodialysis Patients using Federated Learning
Abhiram Raju, Praneeth Vepakomma
Hemodialysis patients who are on donor lists for kidney transplant may get misidentified, delaying their wait time. Thus, predicting their survival time is crucial for optimizing w…
Visual Transformer Meets CutMix for Improved Accuracy, Communication Efficiency, and Data Privacy in Split Learning
Sihun Baek, Jihong Park, Praneeth Vepakomma +3
This article seeks for a distributed learning solution for the visual transformer (ViT) architectures. Compared to convolutional neural network (CNN) architectures, ViTs often have…
Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning
Shraman Pal, Mansi Uniyal, Jihong Park +5
In recent years, there have been great advances in the field of decentralized learning with private data. Federated learning (FL) and split learning (SL) are two spearheads possess…
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning
Ayush Chopra, Surya Kant Sahu, Abhishek Singh +4
Distributed deep learning frameworks like federated learning (FL) and its variants are enabling personalized experiences across a wide range of web clients and mobile/IoT devices.…