Model Agnostic Meta Learning

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My presentation about Model Agnostic Meta Learning Algorithm
  1. Siavash Khodadadeh
  2. Deep Learning
  3. Meta Learning
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Комментарии
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Perfect paper and presentation I have ever watched, even though it was 5 years ago

noahdrisort
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Very clear. I've been confused by several articles and videos. But your word "Try to find a good starting point" along with the MAML's loss function finally got me to understand.
It totally makes sense. We have a good starting point for several tasks, then take few steps towards a particular task. Only one model for multiple tasks. Brilliant.

daesoolee
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Good presentation, many thanks for simplifying model agnostic meta learning

deepuraveendran
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Many thanks! Very clear presentation, which helps me understand the paper a lot easier. Have to log in to say thank you!

mimosa
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Great presentation!! Simplified things a lot.

krishnagarg
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Great presentation! Thank a lot Siavash! One typo in your ppt: 2:23 it's MEAT learning instead of META learning :p

ish
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can anyone say if MAML can be applied on binary classification or not? if we have a data set that contain only Dog vs Cat images, why we need to apply with MAML...

mainaksen
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Congrats! A question: all tasks has to be learned together? Or can be sequencially?

evertonlimaaleixo
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So much better than Siraj. Low bar, but you did a great job! :)

davidselinger
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Can anyone point out the shortcomings of this research paper?

ShanAli-kilr
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a little more about sensitive parameters

youtuber-cr