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 24012450 of 3569 papers

TitleStatusHype
Warm-starting DARTS using meta-learning0
WarpAdam: A new Adam optimizer based on Meta-Learning approach0
Watch, Try, Learn: Meta-Learning from Demonstrations and Reward0
Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards0
Weakly Supervised Few-Shot Segmentation Via Meta-Learning0
Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification0
Weighted Meta-Learning0
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey0
When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications0
When Meta-Learning Meets Online and Continual Learning: A Survey0
Where Do Human Heuristics Come From?0
Which is the best model for my data?0
How Does the Task Landscape Affect MAML Performance?0
Wills Aligner: Multi-Subject Collaborative Brain Visual Decoding0
Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 20190
Wormhole MAML: Meta-Learning in Glued Parameter Space0
Yet Meta Learning Can Adapt Fast, It Can Also Break Easily0
Zebra: In-Context and Generative Pretraining for Solving Parametric PDEs0
Zero-shot meta-learning for small-scale data from human subjects0
Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer0
Learning to Learn Transferable Generative Attack for Person Re-Identification0
Learning to Learn Unlearned Feature for Brain Tumor Segmentation0
Learning to Learn Weight Generation via Local Consistency Diffusion0
Learning to Learn with Conditional Class Dependencies0
Learning to Learn with Feedback and Local Plasticity0
Learning to Learn with Indispensable Connections0
Learning to Learn with Quantum Optimization via Quantum Neural Networks0
Learning to Learn with Variational Information Bottleneck for Domain Generalization0
Learning to Navigate the Web0
Learning to Optimise General TSP Instances0
Learning to Optimize on SPD Manifolds0
Learning to Profile: User Meta-Profile Network for Few-Shot Learning0
Learning to Recommend via Meta Parameter Partition0
Learning to Recover from Failures using Memory0
Learning to Reinforcement Learn by Imitation0
Learning to Remember from a Multi-Task Teacher0
Learning to Retain while Acquiring: Combating Distribution-Shift in Adversarial Data-Free Knowledge Distillation0
Learning to Sample: an Active Learning Framework0
Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs0
Learning to segment anatomy and lesions from disparately labeled sources in brain MRI0
Learning to Segment Skin Lesions from Noisy Annotations0
Learning to Select Best Forecast Tasks for Clinical Outcome Prediction0
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation0
Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning0
Learning to Switch CNNs with Model Agnostic Meta Learning for Fine Precision Visual Servoing0
Learning to Tune XGBoost with XGBoost0
Learning to Unlearn for Robust Machine Unlearning0
Learning to Update for Object Tracking with Recurrent Meta-learner0
Learning Unsupervised Learning Rules0
Learning via Surrogate PAC-Bayes0
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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