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 91–100 of 3569 papers

TitleStatusHype
Boosting Few-Shot Classification with View-Learnable Contrastive LearningCode1
Adaptive FSS: A Novel Few-Shot Segmentation Framework via Prototype EnhancementCode1
CAMeL: Cross-modality Adaptive Meta-Learning for Text-based Person RetrievalCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Adaptive-Control-Oriented Meta-Learning for Nonlinear SystemsCode1
A Channel Coding Benchmark for Meta-LearningCode1
An Enhanced Span-based Decomposition Method for Few-Shot Sequence LabelingCode1
Consolidated learning -- a domain-specific model-free optimization strategy with examples for XGBoost and MIMIC-IVCode1
A Broader Study of Cross-Domain Few-Shot LearningCode1
Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-startCode1
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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