Active learning for epidemic source detection
No Thumbnail Available
Author (Corporation)
Publication date
2023
Typ of student thesis
Course of study
Collections
Type
06 - Presentation
Editors
Editor (Corporation)
Supervisor
Parent work
Special issue
DOI of the original publication
Link
Series
Series number
Volume
Issue / Number
Pages / Duration
Patent number
Publisher / Publishing institution
Place of publication / Event location
Menton
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
Our active learning framework addresses the problem of accurate source detection under resource constraints. The proposed active querying strategies provide a benchmark for this challenge. Promising results on an empirical network of monitored livestock movements suggest the approach has potential applications in this industry.
Keywords
Subject (DDC)
004 - Computer Wissenschaften, Internet
005 - Computer Programmierung, Programme und Daten
005 - Computer Programmierung, Programme und Daten
Event
12th International Conference on Complex Networks and their Applications
Exhibition start date
Exhibition end date
Conference start date
28.11.2023
Conference end date
30.11.2023
Date of the last check
ISBN
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Review
Peer review of the abstract
Open access category
License
Citation
STERCHI, Martin, Lorenz HILFIKER, Rolf GRÜTTER und Abraham BERNSTEIN, 2023. Active learning for epidemic source detection. 12th International Conference on Complex Networks and their Applications. Menton. 2023. Verfügbar unter: https://irf.fhnw.ch/handle/11654/48166