How important is the train-validation split in meta-learning?
Meta-learning aims to perform fast adaptation on a new task through learning a “prior” from
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
[PDF][PDF] How Important is the Train-Validation Split in Meta-Learning?
Y Bai, M Chen, P Zhou, T Zhao, JD Lee, S Kakade… - proceedings.mlr.press
Meta-learning aims to perform fast adaptation on a new task through learning a “prior” from
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
[PDF][PDF] How Important is the Train-Validation Split in Meta-Learning?
Y Bai, M Chen, P Zhou, T Zhao, JD Lee… - … on Machine Learning, 2021 - par.nsf.gov
Meta-learning aims to perform fast adaptation on a new task through learning a “prior” from
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
[PDF][PDF] How Important is the Train-Validation Split in Meta-Learning?
Y Bai, M Chen, P Zhou, T Zhao… - arXiv preprint arXiv …, 2020 - sham.seas.harvard.edu
Meta-learning aims to perform fast adaptation on a new task through learning a “prior” from
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
[PDF][PDF] How Important is the Train-Validation Split in Meta-Learning?
Y Bai, M Chen, P Zhou, T Zhao, JD Lee, S Kakade… - meta-learn.github.io
Meta-learning aims to perform fast adaptation on a new task through learning a “prior” from
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
How Important is the Train-Validation Split in Meta-Learning?
Y Bai, M Chen, P Zhou, T Zhao, JD Lee… - arXiv e …, 2020 - ui.adsabs.harvard.edu
Meta-learning aims to perform fast adaptation on a new task through learning a" prior" from
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
How Important is the Train-Validation Split in Meta-Learning?
Y Bai, M Chen, P Zhou, T Zhao, JD Lee… - arXiv preprint arXiv …, 2020 - arxiv.org
Meta-learning aims to perform fast adaptation on a new task through learning a" prior" from
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
How Important is the Train-Validation Split in Meta-Learning?
Y Bai, M Chen, P Zhou, T Zhao… - 38th International …, 2021 - collaborate.princeton.edu
Meta-learning aims to perform fast adaptation on a new task through learning a “prior” from
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
How Important is the Train-Validation Split in Meta-Learning?
Y Bai, M Chen, P Zhou, T Zhao, JD Lee, SM Kakade… - openreview.net
Meta-learning aims to perform fast adaptation on a new task through learning a" prior" from
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …
multiple existing tasks. A common practice in meta-learning is to perform a train-validation …