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Task formulation for meta-learning enquiry #1
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Hello, I answer your questions one by one as follows: Regarding the formulation of a set of tasks:
Regarding the task distribution p(T):
Regarding the splitting of meta-train/valid/test:
Regarding the question "our meta-learning framework can simulate the unseen entities during meta-training.":
Thanks, Author. |
Hello, I close this issue with the above answer, and please let me know if you have further questions by opening the issue again. Best wishes, |
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Hi there,
Firstly, thank you for your work.
I have read your paper and I have a few questions to clarify.
Mainly, how do you "... formulate a set of tasks such that the model
learns to generalize over unseen entities, which are simulated using seen entities." Your paper also mentioned sampling a task from the distribution p(T) but how is p(T) obtained? Is it predefined?
In other words, in the aspect of code, how did you pre-process your data such that it is split into meta-train/meta-valid/meta-test triplets?
Other than that, do you mind elaborating on "our meta-learning framework can simulate the unseen entities during meta-training." cause I am still a confused by how your model works.
Thanks!!!
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