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 32513275 of 3569 papers

TitleStatusHype
Learning to Segment Skin Lesions from Noisy Annotations0
Domain Adaptive Dialog Generation via Meta LearningCode0
Using learned optimizers to make models robust to input noise0
Watch, Try, Learn: Meta-Learning from Demonstrations and Reward0
One-Shot Neural Architecture Search via Compressive SensingCode0
Adaptive Gradient-Based Meta-Learning MethodsCode0
Query-efficient Meta Attack to Deep Neural NetworksCode0
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings0
A meta-learning recommender system for hyperparameter tuning: predicting when tuning improves SVM classifiersCode0
Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning0
Learning to Self-Train for Semi-Supervised Few-Shot ClassificationCode0
Sequential Scenario-Specific Meta Learner for Online RecommendationCode0
Incremental Few-Shot Learning for Pedestrian Attribute Recognition0
Learning to Transfer: Unsupervised Meta Domain TranslationCode0
Team Fernando-Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection0
Generalizable Person Re-Identification by Domain-Invariant Mapping Network0
Task Agnostic Meta-Learning for Few-Shot Learning0
Regression Networks for Meta-Learning Few-Shot ClassificationCode0
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution TasksCode0
Meta-Learning Representations for Continual LearningCode0
Beyond Exponentially Discounted Sum: Automatic Learning of Return Function0
Image Deformation Meta-Networks for One-Shot LearningCode0
Learning Efficient and Effective Exploration Policies with Counterfactual Meta Policy0
Discrete Infomax Codes for Supervised Representation Learning0
Dataset2Vec: Learning Dataset Meta-FeaturesCode0
Show:102550
← PrevPage 131 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