Federated Transfer Learning: concept and applications

2020-09-26 · Sudipan Saha, Tahir Ahmad

Development of Artificial Intelligence (AI) is inherently tied to the development of data. However, in most industries data exists in form of isolated islands, with limited scope of sharing between different organizations. This is an hindrance to the further development of AI. Federated learning has emerged as a possible solution to this problem in the last few years without compromising user privacy. Among different variants of the federated learning, noteworthy is federated transfer learning (FTL) that allows knowledge to be transferred across domains that do not have many overlapping features and users. In this work we provide a comprehensive survey of the existing works on this topic. In more details, we study the background of FTL and its different existing applications. We further analyze FTL from privacy and machine learning perspective.

📄 PDF Abstract BibTeX arXiv:2010.15561

Code (0)

등록된 구현이 없습니다.

Tasks

Federated Learning Transfer Learning

Federated Machine Learning: Concept and Applications

2019-02-13 · Qiang Yang, Yang Liu, Tianjian Chen, Yongxin Tong

Today's AI still faces two major challenges. One is that in most industries, data exists in the form of isolated islands. The other is the strengthening of data privacy and security. We propose a possible solution to the…

BIG-bench Machine Learning Federated Learning Transfer Learning Vertical Federated Learning

Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning

2022-02-07 · Shuang Dai, Fanlin Meng

Online federated learning (OFL) and online transfer learning (OTL) are two collaborative paradigms for overcoming modern machine learning challenges such as data silos, streaming data, and data security. This survey expl…

Federated Learning Survey Transfer Learning

A Comprehensive Survey on Federated Learning: Concept and Applications

2022-01-23 · Dhurgham Hassan Mahlool, Mohammed hamzah abed

This paper provides a comprehensive study of Federated Learning (FL) with an emphasis on components, challenges, applications and FL environment. FL can be applicable in multiple fields and domains in real-life models. i…

Federated Learning Survey

Combining Federated Learning and Control: A Survey

2024-07-12 · Jakob Weber, Markus Gurtner, Amadeus Lobe, Adrian Trachte 외

This survey provides an overview of combining Federated Learning (FL) and control to enhance adaptability, scalability, generalization, and privacy in (nonlinear) control applications. Traditional control methods rely on…

Decision Making Federated Learning Survey Transfer Learning

FLaaS: Federated Learning as a Service

2020-11-18 · Nicolas Kourtellis, Kleomenis Katevas, Diego Perino

Federated Learning (FL) is emerging as a promising technology to build machine learning models in a decentralized, privacy-preserving fashion. Indeed, FL enables local training on user devices, avoiding user data to be t…

CPU Federated Learning Management object-detection+2