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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 551–560 of 3569 papers

Title	Date	Tasks	Status	Hype
Few-Shot Learning with a Strong Teacher	Jul 1, 2021	Few-Shot LearningMeta-Learning	CodeCode Available	1
Few-Shot Learning with Class Imbalance	Jan 7, 2021	Few-Shot LearningMeta-Learning	CodeCode Available	1
Delving Deep Into Many-to-Many Attention for Few-Shot Video Object Segmentation	Jun 19, 2021	Meta-LearningSemantic Segmentation	CodeCode Available	1
Few-Shot Microscopy Image Cell Segmentation	Jun 29, 2020	Cell SegmentationFew-Shot Learning	CodeCode Available	1
Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection	Mar 30, 2021	Few-Shot Object DetectionMeta-Learning	CodeCode Available	1
Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild	Jul 23, 2020	Few-Shot Object DetectionMeta-Learning	CodeCode Available	1
Few-Shot Object Detection via Variational Feature Aggregation	Jan 31, 2023	Few-Shot Object DetectionMeta-Learning	CodeCode Available	1
Few-Shot One-Class Classification via Meta-Learning	Jul 8, 2020	Anomaly DetectionClassification	CodeCode Available	1
Consolidated learning -- a domain-specific model-free optimization strategy with examples for XGBoost and MIMIC-IV	Jan 27, 2022	Meta-Learning	CodeCode Available	1
Can Learned Optimization Make Reinforcement Learning Less Difficult?	Jul 9, 2024	Decision MakingMeta-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