posted by organizer: TomeEftimov || 7928 views || tracked by 7 users: [display]

UEOB 2019 : CEC-2019 Workshop on Understanding of Evolutionary Optimization Behavior (UEOB 2019)

FacebookTwitterLinkedInGoogle

Link: http://cs.ijs.si/ueob/
 
When Jun 10, 2019 - Jun 13, 2019
Where Wellington, New Zealand
Submission Deadline Mar 15, 2019
Notification Due Mar 31, 2019
Final Version Due Apr 15, 2019
Categories    evolutionary computation   computer science   artificial intelligence   optimization
 

Call For Papers

We are organising the workshop “Understanding of Evolutionary Optimization Behavior (UEOB 2019)” at the IEEE Congress on Evolutionary Computation 2019 (http://cec2019.org/programs/workshops.html#cec-02) in Wellington, New Zealand.

Please consider to contribute to and/or forward to the appropriate groups the following opportunity to present original research articles in CEC 2019.


SCOPE

The focus of the UEOB 2019 is to highlight theoretical and empirical research that investigates approaches needed to analyze stochastic optimization algorithms and performance assessment with regard to different criteria. The main goal is to bring the problem and importance of understanding optimization algorithms closer to researchers and to show them how and why this is important for future development in the optimization community. This will help researchers/users to transfer the gained knowledge from theory into the real world, or to find the algorithm that is best suited to the characteristics of a given real-world problem.

More detailed information can be found at http://cs.ijs.si/ueob/.


TOPICS OF INTEREST

- Data-driven approaches (machine learning/information theory/statistics) for assessing algorithm performance
- Vector embeddings of problem search space
- Meta-learning
- New advances in analysis and comparison of algorithms
- Operators influence on algorithm behavior
- Parameters influence on algorithm behavior
- Theoretical algorithm analysis


SUBMISSION GUIDELINES

All submissions should be formatted according to the CEC 2019 submission guidelines provided at http://www.cec2019.org/papers.html#submission.
All submissions will be handled through EasyChair (https://easychair.org/conferences/?conf=ueob2019) and reviewed by the program committee.

In order to participate to this workshop, a full or a student registration at CEC 2019 is required.

Selected papers will be invited to be extended for a special issue in Natural Computing (https://link.springer.com/journal/11047).


IMPORTANT DATES

- Paper submission: 15 March, 2019
- Notification to authors: 31 March, 2019
- Early registration: 31 March, 2019
- Final submission: 15 April, 2019
- Conference: 10-13 June, 2019


ORGANIZERS

Tome Eftimov
Department of Biomedical Data Sciences, Stanford Medicine
Stanford University
USA

Peter Korošec
Computer Systems Department
Jožef Stefan Institute
Slovenia

Christian Blum
Artificial Intelligence Research Institute (IIIA)
Spanish National Research Council (CSIC)
Spain

Related Resources

Learning & Optimization 2026   ASCE EMI Minisymposium on Probabilistic Learning, Stochastic Optimization, and Digital Twins
Ei/Scopus-AI2A 2026   2026 IEEE 6th International Conference on Artificial Intelligence, Automation and Algorithms (AI2A 2026)
LUHME 2026   3rd Workshop on Language Understanding in the Human-Machine Era (LUHME)
IEEE-ICECCS 2026   2025 IEEE International Conference on Electronics, Communications and Computer Science (ICECCS 2026)
IEEE CEC 2026   IEEE Congress on Evolutionary Computation
Ei/Scopus-ACEPE 2026   2026 3rd IEEE Asia Conference on Advances in Electrical and Power Engineering (ACEPE 2026)
AAIML 2027   IEEE--2027 2nd International Conference on Advances in Artificial Intelligence and Machine Learning
Ei/Scopus-AICSP 2026   2026 International Conference on Algorithms, Intelligent Control and Signal Processing (AICSP 2026)
IEEE-MLNLP 2026   2026 IEEE 9th International Conference on Machine Learning and Natural Language Processing (MLNLP 2026)
MLDS 2026   7th International Conference on Machine Learning Techniques and Data Science