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 2791–2800 of 3569 papers

TitleStatusHype
Meta-Learning of Structured Task Distributions in Humans and MachinesCode0
Improving Few-Shot Learning through Multi-task Representation Learning TheoryCode0
Dialogue Generation on Infrequent Sentence Functions via Structured Meta-Learning—0
Fast Few-Shot Classification by Few-Iteration Meta-LearningCode0
Bayesian Meta-reinforcement Learning for Traffic Signal Control—0
MetaMix: Improved Meta-Learning with Interpolation-based Consistency Regularization—0
Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations—0
Non-greedy Gradient-based Hyperparameter Optimization Over Long Horizons—0
Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift—0
Improving Few-Shot Visual Classification with Unlabelled Examples—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