MMAML 2015 (call for papers in pdf)

Special Session on Multiple Model Approach to Machine Learning

at the 7th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2015)

Bali, Indonesia, March 23-25, 2015

Conference website:

MMAML 2015 website:

Objectives and topics

Ensemble methods have gained great attention of scientific community over the last several years. Multiple models have been theoretically and empirically shown to provide significantly better performance than their single base models. Ensemble algorithms have found their application in various real word problems ranging from person recognition through medical diagnosis and text classification to financial forecasting. The MMAML 2015 Special Session at the 7th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2015) is devoted to the ensemble methods addressing classification, prediction, and clustering problems and their application to Big Data and small data sets as well as data streams and stationary data sets. We want to offer an opportunity for researchers and practitioners to identify new promising research directions as well as to publish recent advances in this area. The scope of the MMAML 2015 includes, but is not limited to the following topics:

  • Theoretical framework for ensemble methods
  • Ensemble learning algorithms: bagging, boosting, stacking, etc.
  • Ensemble methods in clustering
  • Dealing with Big Data and small data sets
  • Subsampling and feature selection in multiple model machine learning
  • Diversity, accuracy, interpretability, and stability issues
  • Homogeneous and heterogeneous ensembles
  • Hybrid methods in prediction and classification
  • Incremental, evolving, and online ensemble learning
  • Mining data streams using ensemble methods
  • Ensemble methods for dealing with concept drift
  • Multi-objective ensemble learning
  • Ensemble methods in agent and multi-agent systems
  • Implementations of ensemble learning algorithms
  • Assessment and statistical analysis of ensemble models
  • Applications of ensemble methods in business, engineering, medicine, etc.

Session chairsContact
Tomasz Kajdanowicz, Wroclaw University of Technology,
Edwin Lughofer, Johannes Kepler University Linz,
Bogdan Trawiński, Wroclaw University of Technology,

Important dates (Extended)

Submission of papers: 22 October 2014 (Strict !!!)
Notification of acceptance:
01 December 2014
Camera-ready papers:
15 December 2014
31 December 2014
Conference date: 23-25 March 2015

International Program Committee

  • Emili Balaguer-Ballester, Bournemouth University, UK
  • Urszula Boryczka, University of Silesia, Poland
  • Abdelhamid Bouchachia, Bournemouth University, UK
  • Robert Burduk, Wrocław University of Technology, Poland
  • Oscar Castillo, Tijuana Institute of Technology, Mexico
  • Rung-Ching Chen, Chaoyang University of Technology, Taiwan
  • Suphamit Chittayasothorn, King Mongkut's Institute of Technology Ladkrabang, Thailand
  • José Alfredo F. Costa, Federal University (UFRN), Brazil
  • Bogusław Cyganek, AGH University of Science and Technology, Poland
  • Ireneusz Czarnowski, Gdynia Maritime University, Poland
  • Patrick Gallinari, Pierre et Marie Curie University, France
  • Fernando Gomide, State University of Campinas, Brazil
  • Francisco Herrera, University of Granada, Spain
  • Tzung-Pei Hong, National University of Kaohsiung, Taiwan
  • Piotr Jędrzejowicz, Gdynia Maritime University, Poland
  • Tomasz Kajdanowicz, Wrocław University of Technology, Poland
  • Yong Seog Kim, Utah State University, USA
  • Bartosz Krawczyk, Wrocław University of Technology, Poland
  • Kun Chang Lee, Sungkyunkwan University, Korea
  • Edwin Lughofer, Johannes Kepler University Linz, Austria
  • Hector Quintian, University of Salamanca , Spain
  • Andrzej Sieminski, Wroclaw University of Technology, Poland
  • Dragan Simic, University of Novi Sad, Serbia
  • Adam Słowik, Koszalin University of Technology, Poland
  • Zbigniew Telec, Wrocław University of Technology, Poland
  • Bogdan Trawiński, Wrocław University of Technology, Poland
  • Krzysztof Trawiński, European Centre for Soft Computing, Spain
  • Olgierd Unold, Wrocław University of Technology, Poland
  • Pandian Vasant, University Technology Petronas, Malaysia
  • Michał Woźniak, Wrocław University of Technology, Poland
  • Zhongwei Zhang, University of Southern Queensland, Australia
  • Zhi-Hua Zhou, Nanjing University, China


All contributions should be original and not published elsewhere or intended to be published during the review period. Authors are invited to submit their papers electronically in pdf format, through EasyChair. All the special sessions are centralized as tracks in the same conference management system as the regular papers. Therefore, to submit a paper please activate the following link and select the track: MMAML 2015: Special Session on Multiple Model Approach to Machine Learning.

Authors are invited to submit original previously unpublished research papers written in English, of up to 10 pages, strictly following the LNCS/LNAI format guidelines. Authors can download the Latex (recommended) or Word templates available at Springer's web site. Submissions not following the format guidelines will be rejected without review. To ensure high quality, all papers will be thoroughly reviewed by the MMAML 2015 International Program Committee. All accepted papers must be presented by one of the authors who must register for the conference and pay the fee. The conference proceedings will be published by Springer in the prestigious series LNCS/LNAI (indexed by ISI CPCI-S, included in ISI Web of Science, EI, ACM Digital Library, dblp, Google Scholar, Scopus, etc.).

Post-conference publication

A selected number of accepted and personally presented papers will be expanded and revised for possible inclusion in special issues in high quality scientific journals. So far, the best papers presented during MMAML special sessions have been invited to special issues on Hybrid and Ensemble Methods in Machine Learning of the following prestigious journals: New Generation Computing (IF=0.941) published in 2011, International Journal of Applied Mathematics and Computer Science (IF=0.487) published in 2012, Journal of Universal Computer Science (IF=0.669) published in 2013, and journal Soft Computing (IF=1.124), to be published in Fall 2014. At present, we are inviting papers to the Special Issue on Hybrid Ensemble Machine Learning for Complex and Dynamic Data in New Generation Computing (IF=0.941), to be published in 2015. Call for papers you can find under the address: