Towards utilitarian online learning - A review of online algorithms in open feature space

He, Yi ; Schreckenberger, Christian ; Stuckenschmidt, Heiner ; Wu, Xindong

Document Type: Conference or workshop publication
Year of publication: 2023
Book title: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Page range: 6647-6655
Conference title: International Joint Conference on Artificial Intelligence
Location of the conference venue: Macao SAR, China
Date of the conference: 19.-25.08.2023
Publisher: Elkind, Edith
Place of publication: Macao SAR
Publishing house: International Joint Conferences on Artificial Intelligence Organization
ISBN: 978-1-956792-03-4
Related URLs:
Publication language: English
Institution: School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: Human intelligence comes from the capability to describe and make sense of the world surrounding us, often in a lifelong manner. Online Learning (OL) allows a model to simulate this capability, which involves processing data in sequence, making predictions, and learning from predictive errors. However, traditional OL assumes a fxed set of features to describe data, which can be restrictive. In reality, new features may emerge and old features may vanish or become obsolete, leading to an open feature space. This dynamism can be caused by more advanced or outdated technology for sensing the world, or it can be a natural process of evolution. This paper reviews recent breakthroughs that strived to enable OL in open feature spaces, referred to as Utilitarian Online Learning (UOL). We taxonomize existing UOL models into three categories, analyze their pros and cons, and discuss their application scenarios. We also benchmark the performance of representative UOL models, highlighting open problems, challenges, and potential future directions of this emerging topic.

Dieser Eintrag ist Teil der Universitätsbibliographie.

Metadata export


+ Search Authors in

+ Page Views

Hits per month over past year

Detailed information

You have found an error? Please let us know about your desired correction here: E-Mail

Actions (login required)

Show item Show item