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Embedding Adaptation is Still Needed for Few-Shot Learning

Embedding Adaptation is Still Needed for Few-Shot Learning

15 April 2021
Sébastien M. R. Arnold
Fei Sha
    VLM
ArXivPDFHTML

Papers citing "Embedding Adaptation is Still Needed for Few-Shot Learning"

4 / 4 papers shown
Title
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
Amrith Rajagopal Setlur
Oscar Li
Virginia Smith
30
13
0
23 Feb 2021
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness
  of MAML
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Aniruddh Raghu
M. Raghu
Samy Bengio
Oriol Vinyals
177
639
0
19 Sep 2019
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCV
BDL
196
498
0
11 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
317
11,681
0
09 Mar 2017
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