Results 91 to 100 of about 31,140,578 (184)

Fed-TDA: Federated Tabular Data Augmentation on Non-IID Data

, 2023
Non-independent and identically distributed (non-IID) data is a key challenge in federated learning (FL), which usually hampers the optimization convergence and the performance of FL.
Han, Peiyi, He, Tianyu, Duan, Shaoming, Liu, Chuanyi, Deng, Qiyuan, Xu, Yifeng   +5 more
core  

Feature matching data synthesis for non-IID federated learning

Federated learning (FL) has emerged as a privacy-preserving paradigm that trains neural networks on edge devices without collecting data at a central server.
Sun, Yuchang, Mao, Yuyi, Shao, Jiawei, Wang, Jessie Hui, Li, Zijian, Zhang, Jun   +5 more
core   +1 more source

FedDB: A Federated Learning Approach Using DBSCAN for DDoS Attack Detection

Applied Sciences
The rise of Distributed Denial of Service (DDoS) attacks on the internet has necessitated the development of robust and efficient detection mechanisms. DDoS attacks continue to present a significant threat, making it imperative to find efficient ways to ...
Yi-Chen Lee, Wei-Che Chien, Yao-Chung Chang   +2 more
doaj   +1 more source

FedBound a boundary aware optimization strategy for federated medical image segmentation under non IID data

Discover Computing
Medical image segmentation is essential for computer-aided diagnosis and treatment planning. Privacy constraints impede centralized training using medical images from diverse healthcare organizations.
Divyansh Pandey, Aaryan Gupta, Varun Tiwari, Jaydeep Kishore, Amit Kumar Bairwa   +4 more
doaj   +1 more source

Comparative Analysis of Centralized and Federated Intrusion Detection in IoT-Enabled Cyber-Physical Systems Under Data and Label-Skew

IEEE Access
Cyber-Physical Systems (CPS) increasingly leverage Internet of Things (IoT) technologies to enable seamless communication and control across distributed devices.
Muhammad Ali Khan, Rao Naveed Bin Rais, Osman Khalid, Mohamed Deriche   +3 more
doaj   +1 more source

Split Averaging: Bridging the Heterogeneity Gap in Clients Data for Federated Learning

IEEE Access
Federated Learning (FL) has gained significant prominence to overcome the issue of data silos in various domains. However, since its introduction FL has been confronted with the presence of Non-Independent and Identically Distributed (Non-IID) data ...
Sajjad Khan, Nikita Karetnikov, Muhammad Habib Ur Rehman, Davor Svetinovic   +3 more
doaj   +1 more source

Chromatic PAC-Bayes Bounds for Non-IID Data.

, 2009
Pac-Bayes bounds are among the most accurate generalization bounds for classifiers learned with \iid data, and it is particularly so for margin classifiers. However, there are many practical cases where the training data show some dependencies and where the traditional \iid assumption does not apply.
Ralaivola, Liva, Szafranski, Marie, Stempfel, Guillaume   +2 more
openaire   +2 more sources

A Review of Solving Non-IID Data in Federated Learning: Current Status and Future Directions

Federated learning (FL), as a machine learning framework, has garnered substantial attention from researchers in recent years. FL makes it possible to train a global model through coordination by a central server while ensuring the privacy of data on ...
Xiulai Li (20258019), Ji He (40669), Wenhai Lu (12750431), Jieren Cheng (20258016)   +3 more
core   +1 more source

Non-IID latent variable models [PDF]

, 2019
University of Technology Sydney. Faculty of Engineering and Information Technology.Latent Variable Model (LVM) is the statistical model that aims to uncover hidden information behind data.
Do, Trong Dinh Thac
core   +1 more source

Evaluation of Remotely Sensed Inundation Data Sets to Estimate Flood‐Associated Emergency Department Visits After Hurricane Harvey

GeoHealth
Floods can increase the risk of adverse health outcomes through multiple pathways, including contamination of food and water. Remotely sensed (RS) inundation extents can help identify regions with expected heightened flood‐related health risks, but ...
Balaji Ramesh, Julia M. Gohlke, Benjamin Zaitchik, Ayaz Hyder, Jeffrey J. Wing, Gia Barboza‐Salerno, Samarth Swarup   +6 more
doaj   +1 more source