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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 3281–3290 of 3569 papers

Title	Date	Tasks	Status	Hype
Meta-GNN: On Few-shot Node Classification in Graph Meta-learning	May 23, 2019	Few-Shot LearningGeneral Classification	CodeCode Available	0
Evaluating recommender systems for AI-driven biomedical informatics	May 22, 2019	AI AgentBIG-bench Machine Learning	CodeCode Available	0
A Neural-Symbolic Architecture for Inverse Graphics Improved by Lifelong Meta-Learning	May 22, 2019	Few-Shot LearningMeta-Learning	CodeCode Available	0
Recurring Concept Meta-learning for Evolving Data Streams	May 21, 2019	DiversityGeneral Classification	—Unverified	0
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models	May 20, 2019	Meta-LearningOne-Shot Learning	CodeCode Available	0
Alpha MAML: Adaptive Model-Agnostic Meta-Learning	May 17, 2019	Few-Shot LearningGeneral Classification	—Unverified	0
Meta Reinforcement Learning with Task Embedding and Shared Policy	May 16, 2019	Deep Reinforcement LearningMeta-Learning	CodeCode Available	0
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning	May 16, 2019	Few-Shot LearningMeta-Learning	CodeCode Available	0
Adaptive Gradient-Based Meta-Learning Methods	May 16, 2019	Meta-Learning	—Unverified	0
Deep Knowledge Based Agent: Learning to do tasks by self-thinking about imaginary worlds	May 16, 2019	Knowledge Base ConstructionMeta-Learning	—Unverified	0

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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