Comments (4)
cbfinn
commented on August 19, 2024
1
This comparison is provided in the paper for some of the experimental domains, and does not perform well in settings where the tasks are mutually exclusive, as you would expect. All of the experimental settings in this paper study task distributions with mutually exclusive tasks. In settings where the tasks are not mutually exclusive, this comparison is expected to perform strongly.
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HX-idiot
commented on August 19, 2024
Thanks for replying,really convincing.
You update the parameters using meta-train, and use this updated parameters to get loss on meta-test, and sum up.When tasks are mutually exclusive, why this policy works?when tasks are exclusive,then the losses you calculated on meta-test will be exclusive ,too. Right? So why your policy can work so good?So i still dont know the insight difference between your policy and my opinion.dose make a gradient descent in advance make any sense?
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HX-idiot
commented on August 19, 2024
do anyone give some explanations? really confused，yayayayayay
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zwd973
commented on August 19, 2024
because he want to find the theta including the commom distribution from mutually exclusive tasks.
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