Call for Papers: International Workshop on Benchmarking of Computational Intelligence Algorithms (BOCIA)
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Thomas Weise
Sep 19, 2017, 7:26:31 PM9/19/17
to Computational Intelligence and Co-evolution
International Workshop on Benchmarking of Computational Intelligence Algorithms (BOCIA)
at the Tenth International Conference on Advanced Computational Intelligence (ICACI 2018)
March 29-31, 2018 in Xiamen, China
BOCIA, the International Workshop on Benchmarking of Computational Intelligence Algorithms, a part of the Tenth International Conference on Advanced Computational Intelligence (ICACI 2018), is cordially inviting the submission of original and unpublished research papers.
Computational Intelligence (CI) is a huge and expanding field which is rapidly gaining importance, attracting more and more interests from both academia and industry. It includes a wide and ever-growing variety of optimization and machine learning algorithms, which, in turn, are applied to an even wider and faster growing range of different problem domains. For all of these domains and application scenarios, we want to pick the best algorithms. Actually, we want to do more, we want to improve upon the best algorithm. This requires a deep understanding of the problem at hand, the performance of the algorithms we have for that problem, the features that make instances of the problem hard for these algorithms, and the parameter settings for which the algorithms perform the best. Such knowledge can only be obtained empirically, by collecting data from experiments, by analyzing this data statistically, and by mining new information from it. Benchmarking is the engine driving research in the fields of optimization and machine learning for decades, while its potential has not been fully explored. Benchmarking the algorithms of Computational Intelligence is an application of Computational Intelligence itself! This workshop wants to bring together experts on benchmarking of optimization and machine learning algorithms. It provides a common forum for them to exchange findings and to explore new paradigms for performance comparison.
1. Topics of Interest
The topics of interest for this workshop include, but are not limited to:
o mining of higher-level information from experimental results
o modelling of algorithm behaviors and performance
o visualizations of algorithm behaviors and performance
o statistics for performance comparison (robust statistics, pca, anova, statistical tests, roc, …)
o evaluation of real-world goals such as algorithm robustness, reliability, and implementation issues
o theoretical results for algorithm performance comparison
o comparison of theoretical and empirical results
o new benchmark problems
o automatic algorithm configuration
o algorithm selection
o the comparison of algorithms in "non-traditional" scenarios such as
- multi- or many-objective domains
- parallel implementations, e.g., using GGPUs, MPI, CUDA, clusters, or running in clouds
- large-scale problems or problems where objective function evaluations are costly
- dynamic problems or where the objective functions involve randomized simulations or noise
- deep learning and big data setups
o comparative surveys with new ideas on
- dos and don'ts, i.e., best and worst practices, for algorithm performance comparison
- tools for experiment execution, result collection, and algorithm comparison
- benchmark sets for certain problem domains and their mutual advantages and weaknesses
All accepted papers in this session will be included in the Proceedings of the IEEE ICACI 2018 published by IEEE Press and indexed by EI.
2. Instructions for Authors
Prospective authors are invited to submit papers of no more than eight pages in IEEE Manuscript Format for Conference Proceedings (double column, A4 format), including results, figures and references, with a maximum file size of 4MB, in PDF format.
More information regarding the submission process can be found at the conference website http://www.ieee.org/conferences_events/conferences/publishing/templates.html and under http://www.icaci2018.org/submission/. Templates can be found at http://www.icaci2018.org/wp-content/uploads/2017/06/2014_04_msw_a4_format.doc (Word) and http://www.icaci2018.org/wp-content/uploads/2017/06/ieee-latex-conference-template.zip (LaTeX). The papers are to be submitted via the official conference website submission form (http://easychair.org/conferences/?conf=icaci2018) where the "International Workshop on Benchmarking of Computational Intelligence Algorithms" should be selected as track.
The papers are to be submitted via the official conference website submission form where the "International Workshop on Benchmarking of Computational Intelligence Algorithms" should be selected as track.
3. Important Dates
Paper Submission Deadline: 15 November 2017
Notification of Acceptance: 15 December 2017
Camera-Ready Copy Due: 15 January 2018
Author Registration: 15 January 2018
Conference Presentation: 29-31 March 2018
For more information please contact Thomas Weise at twe...@hfuu.edu.cn.
4. Chairs
o Thomas Weise, Institute of Applied Optimization, Hefei University, Hefei, China
o Bin Li, University of Science and Technology of China, Hefei, China
o Markus Wagner, University of Adelaide, Adelaide, SA, Australia
o Xingyi Zhang, Anhui University, Hefei, China
o Jörg Lässig, University of Applied Sciences Zittau/Görlitz, Görlitz, Germany
5. International Program Committee
o Thomas Bartz-Beielstein, Technical University of Cologne, Köln (Cologne), Germany
o Josu Ceberio Uribe, University of the Basque Country, Bilbao, Spain
o Wenxiang Chen, Colorado State University, Fort Collins, CO, USA
o Marco Chiarandini, University of Southern Denmark, Odense M, Denmark
o Ramond Chiong, University of Newcastle, Newcastle, Australia
o Carola Doerr, Université Pierre et Marie Curie - Paris 6, Paris, France
o Mohamed El Yafrani, Mohammed V University of Rabat, Rabat, Morocco
o Marcus Gallagher, University of Queensland, Brisbane, Australia
o William La Cava, University of Pennsylvania, Philadelphia, PA, USA
o Jörg Lässig, University of Applied Sciences Zittau/Görlitz, Görlitz, Germany
o Bin Li, University of Science and Technology of China, Hefei, China
o Pu Li, Technische Universität Ilmenau, Ilmenau, Germany
o Jing Liang, Zhengzhou University, Zhengzhou, China
o Zhen Liu, Institute of Applied Optimization, Hefei University, Hefei, China
o Manuel López-Ibáñez, University of Manchester, Manchester, UK
o Yi Mei, Victoria University of Wellington, Wellington, New Zealand
o Martin Middendorf, Leipzig University, Leipzig, Germany
o Antonio J. Nebro, University of Málaga, Málaga, Spain
o Randal S. Olson, University of Pennsylvania, Philadelphia, PA, USA
o Patryk Orzechowski, University of Pennsylvania, Philadelphia, PA, USA
o Qi Qi, University of Science and Technology of China, Hefei, China
o Danilo Sipoli Sanches, Federal University of Technology – Paraná, Cornélio Procópio, Brazil
o Ponnuthurai Nagaratnam Suganthan, Nanyang Technological University, Singapore
o Ryan J. Urbanowicz, University of Pennsylvania, Philadelphia, PA, USA
o Markus Wagner, University of Adelaide, Adelaide, SA, Australia
o Thomas Weise, Institute of Applied Optimization, Hefei University, Hefei, China
o Yang Yu, Nanjing University, Nanjing, China
o Xingyi Zhang, Anhui University, Hefei, China
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