9 citations · 9 across the 5 of their papers we have counts for
5 papers · 1 filter
Federated Learning for Distributed CNC Tool Wear Prediction
Afsana Khan, Morris Stallmann, Marcin Pietrasik +3
Tool wear prediction is an important task in CNC machining, where accurate monitoring of tool condition supports product quality and process reliability. Machine learning methods h…
HybridFL: A Federated Learning Approach for Financial Crime Detection
Afsana Khan, Marijn ten Thij, Guangzhi Tang +1
Federated learning (FL) is a privacy-preserving machine learning paradigm that enables multiple parties to collaboratively train models on privately owned data without sharing raw…
VFL-RPS: Relevant Participant Selection in Vertical Federated Learning
Afsana Khan, Marijn ten Thij, Guangzhi Tang +1
Federated Learning (FL) allows collaboration between different parties, while ensuring that the data across these parties is not shared. However, not every collaboration is helpful…
Incentive Allocation in Vertical Federated Learning Based on Bankruptcy Problem
Afsana Khan, Marijn ten Thij, Frank Thuijsman +1
Vertical federated learning (VFL) is a promising approach for collaboratively training machine learning models using private data partitioned vertically across different parties. I…
Vertical Federated Learning: A Structured Literature Review
Afsana Khan, Marijn ten Thij, Anna Wilbik
Federated Learning (FL) has emerged as a promising distributed learning paradigm with an added advantage of data privacy. With the growing interest in having collaboration among da…