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 1711–1720 of 3569 papers

TitleStatusHype
Constructing a meta-learner for unsupervised anomaly detection—0
Forecast with Forecasts: Diversity Matters—0
Dynamic Channel Access via Meta-Reinforcement Learning—0
Forecasting Market Prices using DL with Data Augmentation and Meta-learning: ARIMA still wins!—0
A Feature Subset Selection Algorithm Automatic Recommendation Method—0
Adapting Mental Health Prediction Tasks for Cross-lingual Learning via Meta-Training and In-context Learning with Large Language Model—0
Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness—0
Bayesian Active Meta-Learning for Black-Box Optimization—0
Learning to Reinforcement Learn by Imitation—0
Loss Function Learning for Domain Generalization by Implicit Gradient—0
Show:102550
← PrevPage 172 of 357Next →
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