Teknologiseminar

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(Dates and subjects - Fall 2020 – Thursdays 12:00-13:00)
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|  15.10    || Bjørn Ivar || ??  || Ulysse || ??
|  15.10    || Bjørn Ivar || ??  || Ulysse || ??
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|-
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|  05.11    || Tom F. Hansen || Introduction, machine learning for automation in underground construction (research)  || Benedikte || ??
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|  05.11    || Tom F. Hansen || Introduction, machine learning for automation in underground construction (research)  || Benedikte || 42
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|  26.11    || Minh || Machine learning for speech mood recognition (research) || Abbas || ??
|  26.11    || Minh || Machine learning for speech mood recognition (research) || Abbas || ??

Revision as of 09:12, 11 September 2020

Meeting structure

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

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

12:15-13:00 Technology / Own Research / Journal review (see guidelines), including discussion

Dates and subjects - Fall 2020 – Thursdays 12:00-13:00

5-10 min housekeeping updates + talks/roundtable

When Who 1 Content 1: Title and type (tech/res/review) Who 2 Content 2: Title and type (tech/res/review)
17.09 Frank Research status and preliminary results/ideas Farzan  ??
15.10 Bjørn Ivar  ?? Ulysse  ??
05.11 Tom F. Hansen Introduction, machine learning for automation in underground construction (research) Benedikte 42
26.11 Minh Machine learning for speech mood recognition (research) Abbas  ??
10.12 Julian  ?? Mike  ??

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
    • R
    • Python as alternative to R, incl. matplotlib
    • ROS
    • Deep learning frameworks and practice
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