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Personalized PCA: Decoupling Shared and Unique Features

Personalized PCA: Decoupling Shared and Unique Features

17 July 2022
Naichen Shi
Raed Al Kontar
ArXivPDFHTML

Papers citing "Personalized PCA: Decoupling Shared and Unique Features"

4 / 4 papers shown
Title
ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning
ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning
Kaan Ozkara
Bruce Huang
Ruida Zhou
Suhas Diggavi
89
0
0
19 Feb 2024
The Internet of Federated Things (IoFT): A Vision for the Future and
  In-depth Survey of Data-driven Approaches for Federated Learning
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning
Raed Al Kontar
Naichen Shi
Xubo Yue
Seokhyun Chung
E. Byon
...
C. Okwudire
Garvesh Raskutti
R. Saigal
Karandeep Singh
Ye Zhisheng
FedML
30
50
0
09 Nov 2021
Distributed Principal Component Analysis with Limited Communication
Distributed Principal Component Analysis with Limited Communication
Foivos Alimisis
Peter Davies
Bart Vandereycken
Dan Alistarh
27
12
0
27 Oct 2021
Survey of Personalization Techniques for Federated Learning
Survey of Personalization Techniques for Federated Learning
V. Kulkarni
Milind Kulkarni
Aniruddha Pant
FedML
179
326
0
19 Mar 2020
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