11 citations · 15 across the 4 of their papers we have counts for
4 papers
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…
Enabling All In-Edge Deep Learning: A Literature Review
Praveen Joshi, Mohammed Hasanuzzaman, Chandra Thapa +2
In recent years, deep learning (DL) models have demonstrated remarkable achievements on non-trivial tasks such as speech recognition and natural language understanding. One of the…
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…
Improving type information inferred by decompilers with supervised machine learning
Javier Escalada, Ted Scully, Francisco Ortin
In software reverse engineering, decompilation is the process of recovering source code from binary files. Decompilers are used when it is necessary to understand or analyze softwa…