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

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Showing 2951–3000 of 3569 papers

TitleStatusHype
Exploiting Field Dependencies for Learning on Categorical DataCode0
Learning Task-Aware Energy Disaggregation: a Federated ApproachCode0
Collision Avoidance Robotics Via Meta-Learning (CARML)Code0
CMVAE: Causal Meta VAE for Unsupervised Meta-LearningCode0
Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta LearningCode0
Exploiting Adapters for Cross-lingual Low-resource Speech RecognitionCode0
MetaXLR -- Mixed Language Meta Representation Transformation for Low-resource Cross-lingual Learning based on Multi-Armed BanditCode0
Meta-X_NLG: A Meta-Learning Approach Based on Language Clustering for Zero-Shot Cross-Lingual Transfer and GenerationCode0
Anti-Retroactive Interference for Lifelong LearningCode0
Variational Metric Scaling for Metric-Based Meta-LearningCode0
Learning One-Shot Imitation from Humans without HumansCode0
XB-MAML: Learning Expandable Basis Parameters for Effective Meta-Learning with Wide Task CoverageCode0
MACFE: A Meta-learning and Causality Based Feature Engineering FrameworkCode0
Adversarial Monte Carlo Meta-Learning of Optimal Prediction ProceduresCode0
Experience-Based Evolutionary Algorithms for Expensive OptimizationCode0
Evolvability ES: Scalable and Direct Optimization of EvolvabilityCode0
MAD: Meta Adversarial Defense BenchmarkCode0
CMML: Contextual Modulation Meta Learning for Cold-Start RecommendationCode0
Magnification Generalization for Histopathology Image EmbeddingCode0
MIGS: Meta Image Generation from Scene GraphsCode0
RECOD Titans at ISIC Challenge 2017Code0
Minimax and Neyman-Pearson Meta-Learning for Outlier LanguagesCode0
MALIBO: Meta-learning for Likelihood-free Bayesian OptimizationCode0
Adaptive Conditional Quantile Neural ProcessesCode0
MAML-CL: Edited Model-Agnostic Meta-Learning for Continual LearningCode0
Learning New Tasks from a Few Examples with Soft-Label PrototypesCode0
TIDE: Test Time Few Shot Object DetectionCode0
Learning Low-Dimensional Embeddings for Black-Box OptimizationCode0
Evaluating recommender systems for AI-driven biomedical informaticsCode0
Manifold meta-learning for reduced-complexity neural system identificationCode0
Learning Invariances for Policy GeneralizationCode0
Adversarial Attacks on Graph Neural Networks via Meta LearningCode0
Min-Max Bilevel Multi-objective Optimization with Applications in Machine LearningCode0
MISE: Meta-knowledge Inheritance for Social Media-Based Stressor EstimationCode0
An Investigation of the Bias-Variance Tradeoff in Meta-GradientsCode0
MARS: Meta-Learning as Score Matching in the Function SpaceCode0
Mitigating Catastrophic Forgetting for Few-Shot Spoken Word Classification Through Meta-LearningCode0
Learning How to Demodulate from Few Pilots via Meta-LearningCode0
Learning Generalized Zero-Shot Learners for Open-Domain Image GeolocalizationCode0
Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain GeneralizationCode0
MATE: Plugging in Model Awareness to Task Embedding for Meta LearningCode0
A Stylometric Inquiry into Hyperpartisan and Fake NewsCode0
Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware SubspaceCode0
Structured Prediction for Conditional Meta-LearningCode0
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal PredictionCode0
Recurrent machines for likelihood-free inferenceCode0
Mixup-Augmented Meta-Learning for Sample-Efficient Fine-Tuning of Protein SimulatorsCode0
Recurrent Meta-Learning against Generalized Cold-start Problem in CTR PredictionCode0
Stateless Neural Meta-Learning using Second-Order GradientsCode0
Capability-Aware Shared Hypernetworks for Flexible Heterogeneous Multi-Robot CoordinationCode0
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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