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

Showing 20512075 of 3569 papers

TitleStatusHype
Reinforcement Teaching0
Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition0
Relation-aware Meta-learning for Market Segment Demand Prediction with Limited Records0
RELF: Robust Regression Extended with Ensemble Loss Function0
REMEDI: Relative Feature Enhanced Meta-Learning with Distillation for Imbalanced Prediction0
REMIX: Automated Exploration for Interactive Outlier Detection0
Representation based and Attention augmented Meta learning0
Representation Change in Model-Agnostic Meta-Learning0
Reservoir Computing for Fast, Simplified Reinforcement Learning on Memory Tasks0
Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning0
Resilient UAV Trajectory Planning via Few-Shot Meta-Offline Reinforcement Learning0
Prior-Knowledge and Attention-based Meta-Learning for Few-Shot Learning0
Rethinking Class Imbalance in Machine Learning0
Rethinking Meta-Learning from a Learning Lens0
Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning0
Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks0
Retrieval-Augmented Meta Learning for Low-Resource Text Classification0
Revealing the Incentive to Cause Distributional Shift0
Relational Experience Replay: Continual Learning by Adaptively Tuning Task-wise Relationship0
Revisiting Meta-Learning as Supervised Learning0
Reward Shaping via Meta-Learning0
Riemannian Geometric-based Meta Learning0
Riemannian Stochastic Gradient Method for Nested Composition Optimization0
ROAM: Recurrently Optimizing Tracking Model0
Robust and Resource-efficient Machine Learning Aided Viewport Prediction in Virtual Reality0
Show:102550
← PrevPage 83 of 143Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-train success rate97.8Unverified
2MZMeta-train success rate97.6Unverified
3MAMLMeta-test success rate36Unverified
4RL^2Meta-test success rate10Unverified
5DnCMeta-test success rate5.4Unverified
6PEARLMeta-test success rate0Unverified
#ModelMetricClaimedVerifiedStatus
1SoftModuleAverage Success Rate60Unverified
2Multi-task multi-head SACAverage Success Rate35.85Unverified
3DisCorAverage Success Rate26Unverified
4NDPAverage Success Rate11Unverified
#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-test success rate (zero-shot)18.5Unverified
2MZMeta-test success rate (zero-shot)17.7Unverified
#ModelMetricClaimedVerifiedStatus
1Metadrop% Test Accuracy95.75Unverified