MMAML 2014 - Special Session on Multiple Model Approach to Machine Learning

Special Session on Multiple Model Approach to Machine Learning
at the 6th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2014)
Bangkok, Thailand, April 7-9, 2014
Conference web site: http://www.ic.kmitl.ac.th/aciids2014/index.html
MMAML 2014 web site: http://kms.ii.pwr.wroc.pl/events/mmaml2014/
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 2014 Special Session at the 6th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2014) is devoted to the ensemble methods and their application to classification, prediction, and clustering problems. 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 2014 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 large volumes of data and lack of adequate data
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
Ensemble methods for dealing with concept drift
Incremental, evolving, and online ensemble learning
Mining data streams using ensemble methods
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 chairs
Contact
Tomasz Kajdanowicz, Wroclaw University of Technology, Poland tomasz.kajdanowicz-AT-pwr.wroc.pl
Edwin Lughofer, Johannes Kepler University Linz, Austria edwin.lughofer-AT-jku.at
Bogdan Trawiński, Wroclaw University of Technology, Poland bogdan.trawinski-AT-pwr.wroc.pl
Important dates
Submission of papers: 15 October 2013
Notification of acceptance: 15 December 2013
Camera-ready papers: 05 January 2014
Conference date: 7-9 April 2014
International Program Committee
Jesús Alcalá-Fdez, University of Granada, Spain
Ethem Alpaydin, Bogaziçi University, Turkey
Emili Balaguer-Ballester, Bournemouth University, UK
Abdelhamid Bouchachia, University of Klagenfurt, Austria
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
Hisao Ishibuchi, Osaka Prefecture University, Japan
Yaochu Jin, University of Surrey, UK
Tomasz Kajdanowicz, Wrocław University of Technology, Poland
Przemysław Kazienko, Wrocław University of Technology, Poland
Yong Seog Kim, Utah State University, USA
Mark Last, Ben-Gurion University of the Negev, Israel
Chunshien Li, National Central University, Taiwan
Kun Chang Lee, Sungkyunkwan University, Korea
Edwin Lughofer, Johannes Kepler University Linz, Austria
Mustafa Mat Deris, Universiti Tun Hussein Onn Malaysia, Malaysia
Jerzy Stefanowski, Poznan University of Technology, Poland
Zbigniew Telec, Wrocław University of Technology, Poland
Bogdan Trawiński, Wrocław University of Technology, Poland
Olgierd Unold, Wrocław University of Technology, Poland
Michał Woźniak, Wrocław University of Technology, Poland
Faisal Zaman, Kyushu Institute of Technology, Japan
Zhongwei Zhang, University of Southern Queensland, Australia
Zhi-Hua Zhou, Nanjing University, China
Dan Zhu, Iowa State University, USA
Submission
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 after that select the track: MMAML 2014 - Special Session on Multiple Model Approach to Machine Learning.
https://www.easychair.org/conferences/?conf=aciids...
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 2014 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.). 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.