Serdecznie zapraszamy 22 stycznia 2024 r. o godzinie 12:00 na Seminarium Centrum Marka Kaca pod tytułem Beyond Imbalanced Classification: Tackling the Challenges of Imbalanced Regression, które wygłosi dr Rita P. Ribeiro z Department of Computer Science, University of Porto. Seminarium odbędzie się w sali D-2-43 Wydziału Fizyki, Astronomii i Informatyki Stosowanej UJ.
Abstract
Imbalanced domain learning is receiving increasing attention from the machine learning research community to cope with challenges encountered in real-world scenarios.
However, the research on this topic has mainly focused on classification tasks and has overlooked the complexities that arise in imbalanced regression.
In numerous real-world applications, imbalanced regression becomes paramount, with rare values often holding critical significance for the domain.
Standard regression methodologies consider all domain values with uniform importance, and conventional evaluation metrics tend to prioritize performance on the common/average values of the data distribution values over the rare/extreme values.
Consequently, much like its classification counterpart, imbalanced regression presents challenges, some even more intricate.
In this talk, we will go through an approach tailored for imbalanced regression that emphasizes predicting extreme values.
Along the way, we'll highlight some accomplishments and the yet-to-be-conquered challenges.
Biography
Rita P. Ribeiro is an Assistant Professor at the Department of Computer Science at the Faculty of Sciences of the University of Porto (FCUP) and a Senior Researcher at the Laboratory of Artificial Intelligence and Decision Support (LIAAD) at the Institute of Systems Engineering and Computing, Technology and Science (INESCTEC). Her main research interests focus on learning problems in imbalanced domains, anomaly detection, evaluation issues in learning tasks and application problems related to social good and environmental impact. She has been involved in several research projects concerning ecological problems, fraud detection and predictive maintenance applications. She is a member of the program committee of several international conferences, also serves as an editor and reviewer for several international journals and has been involved in the organization of various scientific events.