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 871–880 of 3569 papers

TitleStatusHype
Dynamic Spectral Backpropagation for Efficient Neural Network Training—0
Dynamic Task Weighting Methods for Multi-task Networks in Autonomous Driving Systems—0
Fast Training Method for Stochastic Compositional Optimization Problems—0
Early-Stopping for Meta-Learning: Estimating Generalization from the Activation Dynamics—0
Early Warning Prediction with Automatic Labeling in Epilepsy Patients—0
Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks—0
Fast Training Method for Stochastic Compositional Optimization Problems—0
Auto-Meta: Automated Gradient Based Meta Learner Search—0
EEML: Ensemble Embedded Meta-learning—0
A Meta-learner for Heterogeneous Effects in Difference-in-Differences—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