11 citations · 13 across the 6 of their papers we have counts for
5 papers · 1 filter
Federated Split Learning with Only Positive Labels for resource-constrained IoT environment
Praveen Joshi, Chandra Thapa, Mohammed Hasanuzzaman +2
Distributed collaborative machine learning (DCML) is a promising method in the Internet of Things (IoT) domain for training deep learning models, as data is distributed across mult…
Discretization-based ensemble model for robust learning in IoT
Anahita Namvar, Chandra Thapa, Salil S. Kanhere
IoT device identification is the process of recognizing and verifying connected IoT devices to the network. This is an essential process for ensuring that only authorized devices c…
Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance
Praveen Joshi, Chandra Thapa, Seyit Camtepe +3
Federated Learning (FL), Split Learning (SL), and SplitFed Learning (SFL) are three recent developments in distributed machine learning that are gaining attention due to their abil…
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of Things
Yansong Gao, Minki Kim, Chandra Thapa +5
Federated learning (FL) and split learning (SL) are state-of-the-art distributed machine learning techniques to enable machine learning training without accessing raw data on clien…
Advancements of federated learning towards privacy preservation: from federated learning to split learning
Chandra Thapa, M. A. P. Chamikara, Seyit A. Camtepe
In the distributed collaborative machine learning (DCML) paradigm, federated learning (FL) recently attracted much attention due to its applications in health, finance, and the lat…