2nd International Workshop on Learning with Imbalanced Domains - Theory and Applications
Тези до: 02.07.2018
Дати: 10.09.18 — 14.09.18
Область наук: Педагогічні;
Е-мейл Оргкомітету: firstname.lastname@example.org
Організатори: LIDTA Committee
Many real-world data-mining applications involve obtaining and evaluating predictive models using data sets with strongly imbalanced distributions of the target variable. Frequently, the least-common values are associated with events that are highly relevant for end users. This problem has been thoroughly studied in the last decade with a specific focus on classification tasks. However, the research community has started to address this problem within other contexts such as regression, ordinal classification, multi-label classification, multi-instance learning, data streams and time series forecasting. It is now recognised that imbalanced domains are a broader and important problem posing relevant challenges for both supervised and unsupervised learning tasks, in an increasing number of real world applications.
Tackling issues raised by imbalanced domains is crucial to both academia and industry. To researchers, it is an opportunity to develop more adaptable and robust systems/approaches for very complex tasks. For the industry, these tasks are in fact those that many already face today. Examples include the ability to prevent fraud, to anticipate catastrophes, and in general to enable more preemptive actions.
This workshop+tutorial is focused on providing a significant contribution to the problem of learning with imbalanced domains, and to increasing the interest and the contributions to solving some of its challenges. The tutorial component is designed to target researchers and professionals who have a recent interest on the subject, but also those who have previous knowledge and experience concerning this problem. The workshop component invites inter-disciplinary contributions to tackle the problems that many real-world domains face nowadays. With the growing attention that this problem has been collecting, it is important to promote its further development in order to tackle its theoretical and application challenges.
Веб-сторінка конференції: http://lidta.dcc.fc.up.pt/
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