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Meta-Learning

Meta-learning is a methodology considered with "learning to learn" machine learning algorithms.

( Image credit: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 311–320 of 3569 papers

Title	Date	Tasks	Status	Hype
On sensitivity of meta-learning to support data	Oct 26, 2021	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
A Closer Look at Few-Shot Video Classification: A New Baseline and Benchmark	Oct 24, 2021	ClassificationMeta-Learning	CodeCode Available	1
MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation	Oct 23, 2021	Few-Shot LearningFew-Shot Semantic Segmentation	CodeCode Available	1
Exploiting Domain-Specific Features to Enhance Domain Generalization	Oct 18, 2021	Domain GeneralizationMeta-Learning	CodeCode Available	1
Meta-learning via Language Model In-context Tuning	Oct 15, 2021	In-Context LearningInductive Bias	CodeCode Available	1
On the Convergence Theory for Hessian-Free Bilevel Algorithms	Oct 13, 2021	Bilevel OptimizationMeta-Learning	CodeCode Available	1
LiST: Lite Prompted Self-training Makes Parameter-Efficient Few-shot Learners	Oct 12, 2021	Few-Shot LearningIn-Context Learning	CodeCode Available	1
Graph Meta Network for Multi-Behavior Recommendation	Oct 8, 2021	DiversityMeta-Learning	CodeCode Available	1
Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning	Oct 8, 2021	Few-Shot LearningMeta-Learning	CodeCode Available	1
Influence-Balanced Loss for Imbalanced Visual Classification	Oct 6, 2021	ClassificationLong-tail Learning	CodeCode Available	1

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All datasets ML10 MT50 ML45 OMNIGLOT - 1-Shot, 20-way

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MZ+Recon	Meta-train success rate	97.8	—	Unverified
2	MZ	Meta-train success rate	97.6	—	Unverified
3	MAML	Meta-test success rate	36	—	Unverified
4	RL^2	Meta-test success rate	10	—	Unverified
5	DnC	Meta-test success rate	5.4	—	Unverified
6	PEARL	Meta-test success rate	0	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SoftModule	Average Success Rate	60	—	Unverified
2	Multi-task multi-head SAC	Average Success Rate	35.85	—	Unverified
3	DisCor	Average Success Rate	26	—	Unverified
4	NDP	Average Success Rate	11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MZ+Recon	Meta-test success rate (zero-shot)	18.5	—	Unverified
2	MZ	Meta-test success rate (zero-shot)	17.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Metadrop	% Test Accuracy	95.75	—	Unverified