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 1481–1490 of 3569 papers

TitleStatusHype
Leveraging Language for Accelerated Learning of Tool Manipulation—0
p-Meta: Towards On-device Deep Model Adaptation—0
On the Generalizability and Predictability of Recommender SystemsCode1
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks—0
Multi-Access Point Coordination for Next-Gen Wi-Fi Networks Aided by Deep Reinforcement Learning—0
MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot SegmentationCode1
Meta-learning for Out-of-Distribution Detection via Density Estimation in Latent Space—0
MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-LearningCode0
Provable Generalization of Overparameterized Meta-learning Trained with SGD—0
EEML: Ensemble Embedded Meta-learning—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