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 2121–2130 of 3569 papers

TitleStatusHype
Unleash Model Potential: Bootstrapped Meta Self-supervised Learning—0
Unlocking Transfer Learning for Open-World Few-Shot Recognition—0
Unraveling Model-Agnostic Meta-Learning via The Adaptation Learning Rate—0
Unraveling the Control Engineer's Craft with Neural Networks—0
Unsupervised Alternating Optimization for Blind Hyperspectral Imagery Super-resolution—0
Unsupervised Curricula for Visual Meta-Reinforcement Learning—0
Unsupervised Domain Adaptation for Event Detection via Meta Self-Paced Learning—0
Unsupervised Domain Adaptation for Text Classification via Meta Self-Paced Learning—0
Unsupervised Few-Shot Action Recognition via Action-Appearance Aligned Meta-Adaptation—0
Unsupervised Few-shot Learning via Deep Laplacian Eigenmaps—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