Teknologiseminar

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(Dates and subjects - Autumn 2021 – Thursdays 12:00-12:45)
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=== Dates and subjects - Autumn 2021 – Thursdays 12:00-12:45 ===
 
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'''5-20 min housekeeping/updates + 15 min talk (casual meetings = round-table)'''
 
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{| class="wikitable"
 
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|'''When''' || '''What'''||  '''Who''' 
 
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|  02.01 || Introductions, news ||
 
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|  09.09 || (tour de RITMO day) ||
 
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|  16.09 ||  Casual lunch meeting || Bring your own lunch
 
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|  23.09 ||  Title of presentation?? || Marieke
 
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|  30.09 || Casual lunch meeting ||  Bring your own lunch
 
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|  07.10 ||  Title of presentation?? || Mojtaba
 
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|  14.10 ||  --- || ---
 
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|  21.10 || Casual lunch meeting ||  Bring your own lunch
 
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|  28.10 ||  Offline Reinforcement Learning || Ulysse
 
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|  04.11 ||  Unity Machine Learning Agents for Evolutionary Robotics || Frank
 
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|  11.11 || Casual lunch meeting ||  Bring your own lunch
 
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|  18.11 ||  Emotion and mood recognition with speech || Minh 
 
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|  25.11 ||  Design, Kinematic Modeling, and Validation of a Robotic-Assisted Transesophageal Echocardiography System || Reza
 
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| 02.12 ||  Casual lunch meeting ||  Bring your own lunch
 
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| 09.12 ||  Title of presentation?? || Kyrre 
 
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|  16.12 ||  Title of presentation?? || Katrine (remove this note to confirm)
 
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|  To be continued || in January ||  (remove this note to confirm)
 
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[[PreviousSeminars|Overview of earlier seminars]]
[[PreviousSeminars|Overview of earlier seminars]]

Revision as of 10:44, 11 January 2022

Meeting structure

Place: ROBIN pause area, 4th floor Ole-Johan Dahls hus / gather town

12:00-12:15 Brief exchange of recent news, plans, updates, etc.

~12:20-12:35 Presentation on: Technology / Own Research / Journal review (see guidelines), time excludes discussion

Dates and subjects - Spring 2022 – Thursdays 12:00-12:45

5-20 min housekeeping/updates + 15 min talk

When What Who
20.01 Introductions, news
27.01 Vegard Computational resources
03.02
10.02
17.02
24.02


Overview of earlier seminars

Examples of interesting topics for technology introduction

Feel free to add topics to the wishlist!

  • Robotics
    • Reinforcement learning for robotics
    • SLAM
    • embodied cognition
    • Swarm
  • Neural networks
    • Recursive NNs and LSTMs
    • NEAT / HyperNEAT
    • Deep NNs
  • Evolutionary algorithms and other types of optimization
    • Performance comparison of EAs (statistical tests)
    • Differential evolution
    • Diversity preservation methods
    • Novelty search, MAP-Elites and variants
    • Bayesian optimization
  • Tools
    • SLURM
    • R
    • Python as alternative to R, incl. matplotlib
    • ROS
    • Deep learning frameworks and practice
    • Unity ML agents
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