LoAdaBoost: loss-based AdaBoost federated machine learning with reduced
computational complexity on IID and non-IID intensive care data

LoAdaBoost: loss-based AdaBoost federated machine learning with reduced computational complexity on IID and non-IID intensive care data

30 November 2018

Papers citing "LoAdaBoost: loss-based AdaBoost federated machine learning with reduced computational complexity on IID and non-IID intensive care data"

12 / 12 papers shown

Title
A Comprehensive Review on Blockchains for Internet of Vehicles: Challenges and Directions Brian Hildebrand Mohamed Baza Tara Salman Fathi H. Amsaad Abdul Razaqu Abdullah Alourani 33 45 0 21 Mar 2022
FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning Liwei Che Zewei Long Jiaqi Wang Yaqing Wang Houping Xiao Fenglong Ma FedML 27 23 0 12 Sep 2021
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning Zewei Long Jiaqi Wang Yaqing Wang Houping Xiao Fenglong Ma FedML 48 22 0 09 Sep 2021
FedAR: Activity and Resource-Aware Federated Learning Model for Distributed Mobile Robots Ahmed Imteaj M. Amini 83 51 0 11 Jan 2021
FLAME: Taming Backdoors in Federated Learning (Extended Version 1) T. D. Nguyen Phillip Rieger Huili Chen Hossein Yalame Helen Mollering ... Azalia Mirhoseini S. Zeitouni F. Koushanfar A. Sadeghi T. Schneider AAML 27 26 0 06 Jan 2021
Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services Basheer Qolomany Kashif Ahmad Ala I. Al-Fuqaha Junaid Qadir 23 63 0 05 Sep 2020
Privacy-preserving Artificial Intelligence Techniques in Biomedicine Reihaneh Torkzadehmahani Reza Nasirigerdeh David B. Blumenthal T. Kacprowski M. List ... Harald H. H. W. Schmidt A. Schwalber Christof Tschohl Andrea Wohner Jan Baumbach 21 59 0 22 Jul 2020
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data Qi Chang Hui Qu Yikai Zhang M. Sabuncu Chao Chen Tong Zhang Dimitris N. Metaxas MedIm 34 78 0 29 May 2020
HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning Siqi Luo Xu Chen Qiong Wu Zhi Zhou Shuai Yu FedML 33 339 0 26 Feb 2020
Federated Extra-Trees with Privacy Preserving Yang Liu Mingxi Chen Wenxi Zhang Junbo Zhang Yu Zheng FedML 28 3 0 18 Feb 2020
Multi-hop Federated Private Data Augmentation with Sample Compression Eunjeong Jeong Seungeun Oh Jihong Park Hyesung Kim M. Bennis Seong-Lyun Kim 28 17 0 15 Jul 2019
Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records Li Huang Dianbo Liu OOD FedML 19 359 0 22 Mar 2019