SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1971–1980 of 3569 papers

TitleStatusHype
Persian Natural Language Inference: A Meta-learning approach—0
Person30K: A Dual-Meta Generalization Network for Person Re-Identification—0
Personalized Adaptive Meta Learning for Cold-start User Preference Prediction—0
Personalized Federated Learning: A Meta-Learning Approach—0
Personalized Federated Learning via Amortized Bayesian Meta-Learning—0
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach—0
Phase Shift Information Compression in IRS-aided Wireless Systems: Challenges and Opportunities—0
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning—0
p-Meta: Towards On-device Deep Model Adaptation—0
Policy Resilience to Environment Poisoning Attacks on Reinforcement Learning—0
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All datasetsML10MT50ML45OMNIGLOT - 1-Shot, 20-way

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-train success rate97.8—Unverified
2MZMeta-train success rate97.6—Unverified
3MAMLMeta-test success rate36—Unverified
4RL^2Meta-test success rate10—Unverified
5DnCMeta-test success rate5.4—Unverified
6PEARLMeta-test success rate0—Unverified
#ModelMetricClaimedVerifiedStatus
1SoftModuleAverage Success Rate60—Unverified
2Multi-task multi-head SACAverage Success Rate35.85—Unverified
3DisCorAverage Success Rate26—Unverified
4NDPAverage Success Rate11—Unverified
#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-test success rate (zero-shot)18.5—Unverified
2MZMeta-test success rate (zero-shot)17.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Metadrop% Test Accuracy95.75—Unverified