Date
Tuesday July 9, 2024 from 3:30 PM to 4:30 PMLocation
Neuron 0.262Co-organizer
Mathematics and Computer SciencePrice
freeLearning from poor information: a glance behind, a glimpse ahead
Benjamin Quost, Professor at Universit茅 de Technologie de Compi猫gne (UTC, France) is a guest of Cassio de Campos, Full Professor of research group Uncertainty in AI, Department M&CS, 黑料福利网.
Title | Learning from poor information: a glance behind, a glimpse ahead
The recent trends in machine learning involve complex models learnt from huge amounts of data. However, in a wide range of applications, the information at hand may be scarce, noisy, or imprecise. Processing such poor data remains a challenge; an alternative then consists to learn models with nice robustness properties, and (whenever possible) to involve humans during training or when making decisions. In this talk, we take a glance at several such cases where such poor data can be processed to produce robust or cautious models; we also discuss how uncertainty can be leveraged for this purpose. Eventually, we glimpse at several (open) research directions aiming at producing trustful AI systems, making connections with the topics of fairness and explainability.
Program
15:30 - 16:15 Lecture in Neuron 0.262 (doors open at 15:15)
16:15 - 16:30 Q&A
16:30 - 17:00 Drinks
is required and free of charge.
Benjamin Quost
Prof. Benjamin Quost obtained his engineering degree (2003), PhD (2006) and Habilitation (2018) from the Universit茅 de Technologie de Compi猫gne (UTC, France), where he holds a professorship at the Heudiasyc laboratory, Department of Computer Science. His research interests focus on machine learning from imperfect (imprecise, uncertain) information, and more particularly supervised and unsupervised classification. He also works on classifier combination and data fusion. He is interested in the theoretical framework of belief functions/Dempster-Shafer theory for representing and managing imprecision and uncertainty. He serves as editor/program committee member of numerous journals/conferences, has published more than eighty scientific works and participates in multiple national and international research projects.
Eindhoven Artificial Intelligence Systems Institute
The Eindhoven Artificial Intelligence Systems Institute (EAISI) is the central hub for artificial intelligence research at Eindhoven University of Technology (黑料福利网). EAISI brings together researchers across engineering, computer science, and applied domains to develop AI methods, systems, and applications for industry and society.