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Active and Self-Supervised Learning for Data Selection

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Smart data labeling - Igor Susmelj

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  • Overview of recent methods in self-supervised learning with images and how to use them
  • What can we do with the learned representations?
  • Learn what is active-learning in the context of data selection
  • Learn how we can combine the two approaches to improve the selection process

About the speaker:

Igor is a co-founder at Lightly – an ETH Spin-Off based in Zurich that is working on a novel data curation platform. Before, he worked for two years in the innovation lab of a financial institution as a software engineer. Igor holds a degree in electrical engineering from ETH Zurich. During his studies, he developed a lot of experience in machine learning and robotics and had multiple successful publications in the area of deep learning.

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