Description
2-day workshop focusing on self-supervised learning for AI in different types of value creation.To date, most successful applications of deep learning in signals and decoding are based on supervised learning. However, supervised learning is contingent on the availability of labeled data. The need for labeled data is a serious limitation to applications at scale and complicates the maintenance of real-life
supervised learning systems. The typical situation is that unlabeled data is abundant, and this has given rise to paradigms such as self-supervised learning (SSL). SSL is based on combining large amounts of unlabeled data with limited labeled data and relies on supervised learning with a supervisory signal derived from the data itself. While we have seen many successful applications of SSL, theoretical understanding of the mechanisms that make SSL work is only starting to emerge.
In this workshop, we will discuss both the emerging theoretical understanding and practical applications of SSL in decoding of complex signals. The program features invited talks, posters, and social activities. The workshop is organized by the Pioneer Centre for Artificial Intelligence’s collaboratory, Signals and
Decoding.
Centre website: https://www.aicentre.dk
Period | 12 Oct 2022 |
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Event type | Workshop |
Location | Aalborg, DenmarkShow on map |
Degree of Recognition | International |
Keywords
- Artificial Intelligence
- self-supervised Learning
Documents & Links
Related content
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Publications
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Artificial Intelligence, Value Creation and Adaptation: Does Computational Rationality Complement Bounded Rationality?
Research output: Contribution to conference without publisher/journal › Conference abstract for conference › Research › peer-review
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Activities
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Projects