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 3201–3210 of 3569 papers

TitleStatusHype
TGG: Transferable Graph Generation for Zero-shot and Few-shot LearningCode0
Exploring Domain Shift in Extractive Text Summarization—0
Meta-Learning with Warped Gradient DescentCode0
Deep Learning Theory Review: An Optimal Control and Dynamical Systems PerspectiveCode0
Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks—0
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning—0
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms—0
An Introduction to Advanced Machine Learning : Meta Learning Algorithms, Applications and Promises—0
Fairness Warnings and Fair-MAML: Learning Fairly with Minimal DataCode0
Learning to Demodulate from Few Pilots via Offline and Online Meta-LearningCode0
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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