MMAML 2022

Special Session on Multiple Model Approach to Machine Learning

at the 14th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2022)
Ho Chi Minh City, Vietnam
Conference website: http://www.aciids.pwr.edu.pl

Special Session Organizers

Tomasz Kajdanowicz
Wrocław University of Science and Technology, Poland
E-mail: tomasz.kajdanowicz@pwr.edu.pl

Edwin Lughofer
Johannes Kepler University Linz, Austria
E-mail: edwin.lughofer@jku.at

Bogdan Trawiński
Wrocław University of Science and Technology, Poland
E-mail: bogdan.trawinski@pwr.edu.pl

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 2022 Special Session at the 14th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2022) 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 2022 includes, but is not limited to the following topics:

Theoretical framework for ensemble methods
Ensemble methods for deep learning
Ensemble learning algorithms: bagging, boosting, stacking, etc.
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
Big data mining and big data analytics
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

ACIIDS 2022 important dates

Submission of papers: 22 May 2022 (Hard deadline)
Notification of acceptance: 11 July 2022
Camera-ready papers: 25 July 2022
Registration & payment: 25 July 2022
Conference date: 28-30 November 2022