all AI news
Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users
Feb. 27, 2024, 5:42 a.m. | Hantao Yang, Xutong Liu, Zhiyong Wang, Hong Xie, John C. S. Lui, Defu Lian, Enhong Chen
cs.LG updates on arXiv.org arxiv.org
Abstract: We study the problem of federated contextual combinatorial cascading bandits, where $|\mathcal{U}|$ agents collaborate under the coordination of a central server to provide tailored recommendations to the $|\mathcal{U}|$ corresponding users. Existing works consider either a synchronous framework, necessitating full agent participation and global synchronization, or assume user homogeneity with identical behaviors. We overcome these limitations by considering (1) federated agents operating in an asynchronous communication paradigm, where no mandatory synchronization is required and all agents …
abstract agent agents arxiv asynchronous communication cs.ai cs.lg framework global recommendations server study synchronization type
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
AI Research Scientist
@ Vara | Berlin, Germany and Remote
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
Lead Data Scientist, Commercial Analytics
@ Checkout.com | London, United Kingdom
Data Engineer I
@ Love's Travel Stops | Oklahoma City, OK, US, 73120