April 4, 2024, 4:41 a.m. | Ren\'e Schwermer, Ruben Mayer, Hans-Arno Jacobsen

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.02779v1 Announce Type: new
Abstract: In response to the increasing volume and sensitivity of data, traditional centralized computing models face challenges, such as data security breaches and regulatory hurdles. Federated Computing (FC) addresses these concerns by enabling collaborative processing without compromising individual data privacy. This is achieved through a decentralized network of devices, each retaining control over its data, while participating in collective computations. The motivation behind FC extends beyond technical considerations to encompass societal implications. As the need for …

abstract arxiv breaches building challenges collaborative computing concerns cs.lg data data privacy data security decentralized enabling extensions face privacy processing regulatory security security breaches sensitivity survey systems through type

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Business Data Scientist, gTech Ads

@ Google | Mexico City, CDMX, Mexico

Lead, Data Analytics Operations

@ Zocdoc | Pune, Maharashtra, India