Teknologiseminar

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(Dates and subjects - Spring 2020 – Fridays 12:00-13:00)
(Dates and subjects - Spring 2020 – Fridays 12:00-13:00)
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12:15-13:00 Technology / Own Research / Journal review (see [http://robin.wiki.ifi.uio.no/Journal_Review guidelines]), including discussion
12:15-13:00 Technology / Own Research / Journal review (see [http://robin.wiki.ifi.uio.no/Journal_Review guidelines]), including discussion
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=== Dates and subjects - Spring 2020 – Fridays 12:00-13:00 ===  
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=== Dates and subjects - Spring 2020 – Thursdays 12:00-12:30/13:00 ===  
''' Eat your own lunch while listening / discussing '''
''' Eat your own lunch while listening / discussing '''
{| class="wikitable"
{| class="wikitable"

Revision as of 10:09, 17 April 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 - Spring 2020 – Thursdays 12:00-12:30/13:00

Eat your own lunch while listening / discussing

When Who Content (title and type (tech/res/review)
24.01 Jendrik Seipp Introduction and own research
14.02 Chloe Barnes Introduction and own research
21.02 28.02 Seyed Mojtaba Karbasi Introduction and own research
20.03 Tønnes Nygaard Bias and discrimination in machine learning
03.04 Vegard Søyseth Robin's laboratories
23.04 Ulysse Côté-Allard Introduction and own research
30.04 Hoang Minh Pham Introduction and own research
07.05 Round table

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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