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AAU Innovate Auditorium

Zheng-Hua Tan and Lars Kai Hansen, Signals & Decoding Co-laboratory, Pioneer Centre for AI, Denmark

2022 Workshop on Self-Supervised Learning for Signal Decoding

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.

AAU Innovate Auditorium

Thomas Manns Vej 25, 9220 Aalborg Øst., Denmark

  • 13.10.2022 12:00 - 14.10.2022 16:00
    Registration deadline: 01.10.2022

  • English

  • On location

Free but with no-show fee

AAU Innovate Auditorium

Thomas Manns Vej 25, 9220 Aalborg Øst., Denmark

13.10.2022 12:00 - 14.10.2022 16:00
Registration deadline: 01.10.2022

English

On location

Free but with no-show fee

Zheng-Hua Tan and Lars Kai Hansen, Signals & Decoding Co-laboratory, Pioneer Centre for AI, Denmark

2022 Workshop on Self-Supervised Learning for Signal Decoding

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.

AAU Innovate Auditorium

Thomas Manns Vej 25, 9220 Aalborg Øst., Denmark

  • 13.10.2022 12:00 - 14.10.2022 16:00
    Registration deadline: 01.10.2022

  • English

  • On location

Free but with no-show fee

AAU Innovate Auditorium

Thomas Manns Vej 25, 9220 Aalborg Øst., Denmark

13.10.2022 12:00 - 14.10.2022 16:00
Registration deadline: 01.10.2022

English

On location

Free but with no-show fee

Registration:

- Registration is done by filling in this Excel-file and send to Susanne Nørrevang sn@es.aau.dk. Deadline: October 1, 2022.

- Registration is free with lunches, dinner and coffee breaks included. There is a no-show fee of DKK 2000. Cancellations are accepted no later than October 6, 2022.

- For online participation, no registration is needed. Zoom link will be shared.

Description

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.

The workshop is organized by the Pioneer Centre for Artificial Intelligence’s collaboratory, Signals and Decoding.

Invited speakers

at the workshop
Invited speakers
  • Lars Kai Hansen, Technical University of Denmark, Denmark
  • Zheng-Hua Tan, Aalborg University, Denmark
Invited speakers
  • Robert Jenssen, UiT The Arctic University of Norway, Norway
  • Wojciech Samek, Frauenhofer Heinrich Herz Institute, Germany
  • Wei-Ning Hsu, Facebook AI Research (FAIR), USA
Invited speakers
  • Pengtao Xie, UC San Diego, USA
  • Heidi Christiansen, University of Sheffield, UK
  • Lasse Borgholt, Aalborg University, the Pioneer Centre for AI, and Corti A/S, & Jakob D. Havtorn, Technical University of Denmark and Corti A/S