• FRI Piškot: Ribeiro – Strojno učenje in analiza podatkov
Napovedi

Profesorica Bernadete Ribeiro z Univerze v Coimbri na Portugalskem bo ta teden na predavanju FRI Piškot predstavila svoje raziskovalno delo na področjih strojnega učenja in analize podatkov. Dobimo se v četrtek, 27. oktobra, ob 10.15 v predavalnici P22 na FRI!


Current  Research Topics in Learning and Data Analytics

Abstract:
In this talk I will present my current research topics in machine learning and pattern recognition. I will motivate for zero-shot learning (ZSL) which has been widely used in the field of computer vision and can also be approached in a more broader class of computer science problems. An application of ZSL using Grassmannian manifold will be shortly presented and discussed.

 

Short CV:
Bernardete Ribeiro is Tenured Associate Professor with Habilitation at the Informatics Engineering Department of the University of Coimbra in Portugal, from where she received Ph.D. in Electrical Engineering, speciality of Informatics. Her research interests are in the areas of Machine Learning and Pattern Recognition  and their applications to a broad range of fields. She is Founder and Leader of the Laboratory of Artificial Neural Networks (LARN). She was responsible/participated in several research projects both in international and national levels (FP6, FP7, USA, FCT, QREN) in a wide range of application areas. She authored or co-authored many publications including books, journals and international and national conferences. Bernardete Ribeiro served in international and national evaluation panels and as board member, associate editor and reviewer of several journals and conferences. She is coordinator of the BSc in Informatics Engineering at the University of Coimbra and Deputy Head of Portuguese Association of Pattern Recognition. Bernardete Ribeiro is IEEE Senior Member, IEEE SMC Senior member, member of IARP International Association of Pattern Recognition, member of International Neural Network Society (INNS) and member of Association for Computing Machinery (ACM).