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Topic

DataNinja Spring School

Description

Trustworthy AI: Building Safe and Reliable Solutions
For more information, check the following page:
https://dataninja.nrw/?page_id=999

Time

May 8, 2023 09:00 AM
May 9, 2023 09:00 AM
May 10, 2023 09:00 AM

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Speakers

Virgina Dignum

Prof. @Umeå University, Sweden

Social and Ethical Artificial Intelligence

Martin Riedmiller

Dr. @Google DeepMind

Reinforcement Learning

Ann Nowé

Prof. @Vrije Universiteit Brussel

Reinforcement Learning (RL); Learning in Multi-agent Systems; Transparent and Explainable AI

Christian Igel

Prof. @University of Copenhagen

Applications of Machine Learning for Sustainable Development

Viktor Bengs

Dr. @Ludwig-Maximilians-Universität München

Bandit Algorithms; Uncertainty Quantification

Noémie Jaquier

PhD @Karlsruhe Institute of Technology

Geometric Methods for Robotics & Machine Learning

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Message preview	Hi there, You are invited to a Zoom webinar. When: May 8, 2023 09:00 AM Vienna Topic: DataNinja Spring School Register in advance for this webinar: https://uni-bielefeld.zoom.us/webinar/register/WN_FxCqf89gR9i6NtawCzQHaA Or an H.323/SIP room system: H.323: 213.19.144.110 (Amsterdam Netherlands) 213.244.140.110 (Germany) 207.226.132.110 (Japan Tokyo) 149.137.24.110 (Japan Osaka) Meeting ID: 698 0413 6715 SIP: 69804136715@fr.zmeu.us After registering, you will receive a confirmation email containing information about joining the webinar. ---------- Webinar Speakers Virgina Dignum (Prof. @Umeå University, Sweden) Social and Ethical Artificial Intelligence Martin Riedmiller (Dr. @Google DeepMind) Reinforcement Learning Ann Nowé (Prof. @Vrije Universiteit Brussel) Reinforcement Learning (RL); Learning in Multi-agent Systems; Transparent and Explainable AI Christian Igel (Prof. @University of Copenhagen) Applications of Machine Learning for Sustainable Development Viktor Bengs (Dr. @Ludwig-Maximilians-Universität München) Bandit Algorithms; Uncertainty Quantification Noémie Jaquier (PhD @Karlsruhe Institute of Technology) Geometric Methods for Robotics & Machine Learning