Bharath Hariharan: When life gives you lemons: Making lemonade from limited labels скачать в хорошем качестве

Bharath Hariharan: When life gives you lemons: Making lemonade from limited labels

Abstract: Many research directions have been proposed for dealing with the limited availability of labeled data in many domains, including zero-shot learning, few-shot learning, semi-supervised learning and self-supervised learning. However, I argue that in spite of the volume of research in these paradigms, existing approaches discard vital domain knowledge that can prove useful in learning. I will show two case studies where thinking about where the data comes from in the problem domain leads to substantial improvements in accuracy. The first case study will look at the domain of self-driving, and will show how leveraging domain knowledge can allow systems to automatically discover objects and train detectors with no labels at all. The second study will look at zero-shot learning, where digging deeper into the provenance of class descriptions yields surprising and useful insight. Bio: Bharath Hariharan is an assistant professor of Computer Science at Cornell University, where he works on all things computer vision, but focusing on problems where data challenges prevail. He is a recipient of the NSF CAREER award as well as the PAMI Young Researcher award.