Workshop on Machine Learning Algorithms, Systems and Application

Many computer applications result in large volumes of data that require a set of techniques and tools to extract useful information for decision support, prediction, exploration and understanding of the phenomena governing the data sources. This workshop aims to bring together professionals, researchers, and practitioners to discuss efficient techniques, methods and tools to manage, exploit and interpret the increasing volumes of data in environments that may change continuously. The goal is to build models that are able to tackle and govern the high variability in stationary or non-stationary or complex hybrid systems. Such systems are being explored in various applications such as: medical diagnostics, robotics, business, industrial control, fault detection, quality control, surface inspection, system identification, transportation, communications, web applications, environmental monitoring, biomedical systems, decision support systems, security, and electronic services.