(Apologies for cross-posting)

MAB-KD: Workshop on Multi-Armed Bandits for Knowledge Discovery (Hybrid)

In conjunction with 23rd IEEE International Conference on Data Mining (ICDM 2023), Dec 1-4, 2023, Shanghai, China.

Workshop Link: https://www.gla.ac.uk/schools/computing/research/researchsections/ida-section/knowledgeanddataengineeringsystems/mabkd/


== IMPORTANT DATES ==

Paper Submission: September 8, 2023
Author Notification: September 24, 2023
Camera Ready: October 1, 2023
Workshop Day: December 4, 2023

== AIMS AND SCOPE ==

Multi-Armed Bandit (MAB) problem is a class of sequential decision-making problems concerned with choosing one or more actions among several alternatives. MAB problems are paradigms of the fundamental trade-off between exploitation and exploration that can be observed in many knowledge-discovery tasks. MAB algorithms have been used in many applications like e-commerce, online advertisement, news recommendation, and next-query prediction, among many others, considering knowledge acquisition and information gathering. Due to its simplicity and applicability, there is a surge in the domains where MAB algorithms are considered, including conversational AI, IoT, Transportation systems, and dynamic pricing.

Submitted papers will be evaluated based on criteria such as technical originality, creativity, and applicability. The topics are concentrated on (but not limited to) the following themes:
[*] Foundations and theoretical aspects of MABs.
[*] Learning Paradigms of MABs in Distributed Knowledge Discovery, IoT, conversational AI, Dynamic pricing.
[*] MAB algorithms for problems with structured and dependent arms.
[*] Problem settings and algorithms for arms with switching costs.
[*] MAB-led Data Mining & Information Gathering.
[*] Deep MABs for dynamic optimization.
[*] Application of MABs in e.g., Intelligent Transportation Systems, Dynamic Pricing, Smart Cities, Recommendation Systems.

== SUBMISSIONS & HYBRID ATTENDANCE ==

By the unique ICDM tradition, all accepted workshop papers will be published in the dedicated ICDMW proceedings published by the IEEE Computer Society Press. Paper submissions should be limited to max 8 pages plus 2 extra pages (for references, appendix, etc.) and follow the IEEE ICDM format. More detailed information is available in the IEEE ICDM 2023 Submission Guidelines. All submissions will be reviewed by the Program Committee based on technical quality, relevance to scope of the workshop, originality, significance, and clarity. Please submit your papers via the submission link:

On-Line Paper Submission (wi-lab.com)

https://wi-lab.com/cyberchair/2023/icdm23/scripts/submit.php?subarea=S08&undisplay_detail=1&wh=/cyberchair/2023/icdm23/scripts/ws_submit.php

***Online Attendance Option***: In light of potential hesitancy for international traveling, we are considering providing an online attendance option for the MAB-KD ICDM workshop. This would cater to those who may face travel restrictions or have concerns about in-person attendance.

== INVITED TALK ==
Dr. Zhenhui (Jessie) Li, Yunqi Academy of Engineering, 'Making Decision for the City: A Real Case in Traffic Optimization'

== ORGANISATION ==
Shameem A Puthiya Parambath, University of Glasgow, UK
Christos Anagnostopoulos, University of Glasgow, UK
Sanjay Chawla, Qatar Computing Research Institute, Qatar

---------------


To unsubscribe from the DBWorld mailing list please visit https://dbworld.sigmod.org and follow the unsubscribe directions given there.