CeMEAI

IFIP Working Group 12.2

Machine Learning and Data Mining

André C. P. L. F. de Carvalho

Chair

Institute of Mathematics and Computer Sciences, University of São Paulo at São Carlos, São Carlos, SP, Brazil

Xin-Yao

Vice-Chair

University of Birmingham, UK

Members

Amparo Alonso Betanzos, University of Coruña, Spain

Matjaz Gams, Jožef Stefan Institute, Slovenia

Eduan Kotzé, University of the Free State in South Africa, South Africa

Teresa Ludermir, Federal University of Pernambuco, Brazil

Dino Ienco, Irstea Institute, France

Shi Zhongzhi, Institute of Computing Technology, at the Chinese Academy of Sciences, China

Aim and scope

Machine Learning and Data Mining Working Group (WG) is part of the Technical Committee (TC) 12 - Artificial Intelligence. The WG 12.2 brings together researchers from Artificial Intelligence that share an interest in Machine Learning and Data Mining. For such, this WG is composed by researchers representing the scientific communities in the countries associated with scientific societies that are members of the International Federation for Information Processing (IFIP). The scope of the Working Group’s activities includes (but is not restricted to) the following:

Data Science

Multistrategy Machine learning

Association Rules

Classification Rules

Decision Trees

Case-Based Reasoning

Genetic Algorithms

Inductive Logic Programming

Neural Nets

Instance Based Learning

Support Vector Machines

Bagging and Boosting

Feature Reduction

Supervised and Unsupervised Learning

Web and Text Mining

Mining of Images, Video etc

Concept Learning

Bayesian Learning

Computational Learning Theory

Reinforcement Learning