*Apologies for multi-posting* ************************************************************************************* LIDTA 2021, co-located with ECML/PKDD 2021 3rd International Workshop on Learning with Imbalanced Domains: Theory and Applications 17-17 September, Online Website: http://lidta.dcc.fc.up.pt/ DEADLINE FOR SUBMISSIONS: Wednesday, June 23, 2021 ************************************************************************************* *********************************************** KEY DATES Submission Deadline: Wednesday, June 23, 2021 Notification of Acceptance: Friday, July 9, 2021 Camera-ready Deadline: Friday, July 23, 2021 ECML/PKDD 2021: 13-17 September, 2021 LIDTA 2021: TBC *********************************************** The problem of imbalanced domain learning has been thoroughly studied in the last two decades, with a specific focus on classification tasks. However, the research community has started to address this problem in other contexts such as regression, ordinal classification, multi-label and multi-class classification, association rules mining, multi-instance learning, data streams, time-series and spatio-temporal forecasting, text mining and multimodal data. Clearly, the research community recognises that imbalanced domains are a broad and important problem. Such a context poses important challenges for both supervised and unsupervised learning tasks, in an increasing number of real-world applications. Tackling the 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. These tasks are, in many cases, those that industry is already facing today. These are very diverse and include the ability to prevent fraud, to anticipate catastrophes, and in general to enable a more preemptive action in an increasingly fast-paced world. This workshop proposal focuses on providing a significant contribution to the problems of learning with imbalanced domains, aiming to increase the interest and the contributions to solving its challenges. The workshop invites inter-disciplinary contributions to tackle the problems that many real-world domains face nowadays. With the growing attention that this challenge has collected, it is crucial to promote its further development in order to tackle its theoretical and application challenges. *********************************************** The research topics of interest to LIDTA'2021 workshop include (but are not limited to) the following: *** Foundations of learning in imbalanced domains Probabilistic and statistical models New knowledge discovery theories and models Probabilistic and statistical models New knowledge discovery theories and models Deep learning Handling imbalanced big data One-class learning Learning with non i.i.d. data Rare event detection in classification tasks New approaches for data pre-processing (e.g. resampling strategies) Post-processing approaches Sampling approaches Feature selection and feature transformation Evaluation metrics and methodologies Ensemble methods Instance hardness *** Knowledge discovery and machine learning in imbalanced domains Classification, ordinal classification Regression Data streams and time series forecasting Clustering Adaptive learning and algorithm-level approaches Multi-label, multi-instance, sequence and association rules mining Active learning Spatial and spatio-temporal learning Text and image mining Multi-modal learning Predictive Maintenance Automated machine learning Energy-efficiency *** Applications in imbalanced domains Health applications (e.g. medical imaging) Fraud detection (e.g. finance, credit and online banking) Anomaly detection (e.g. industry, intrusion detection, privacy and security) Environmental applications (e.g. meteorology, biology, oil spill detection) Social media applications (e.g. popularity prediction, recommender systems) Fake news detection and disinformation, deep fake classification Other real world applications and case studies *********************************************** SUBMISSION Details soon! Check for updates on http://lidta.dcc.fc.up.pt/ *********************************************** PROCEEDINGS Details soon! Check for updates on http://lidta.dcc.fc.up.pt/ *********************************************** PROGRAM COMMITTEE Details soon! Check for updates on http://lidta.dcc.fc.up.pt/ *********************************************** ORGANIZERS Nuno Moniz | INESC TEC / University of Porto, Portugal Paula Branco | University of Ottawa, Canada Luís Torgo | Dalhousie University, Canada Nathalie Japkowicz | American University, USA Michał Woźniak | Wroclaw University of Science and Technology, Poland Shuo Wang | University of Birmingham, UK