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 3101–3150 of 3569 papers

TitleStatusHype
Meta-Learning to Detect Rare Objects—0
Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video—0
Meta-learning algorithms for Few-Shot Computer VisionCode0
MGHRL: Meta Goal-generation for Hierarchical Reinforcement Learning—0
Chameleon: Learning Model Initializations Across Tasks With Different SchemasCode0
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation—0
Learning Fast Adaptation with Meta Strategy OptimizationCode0
Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning—0
Improving Federated Learning Personalization via Model Agnostic Meta LearningCode0
Overcoming Data Limitation in Medical Visual Question AnsweringCode1
Fast and Effective Adaptation of Facial Action Unit Detection Deep Model—0
Localized Meta-Learning: A PAC-Bayes Analysis for Meta-Leanring Beyond Global Prior—0
Learning Effective Exploration Strategies For Contextual Bandits—0
Meta-Learning by Hallucinating Useful Examples—0
Localized Generations with Deep Neural Networks for Multi-Scale Structured Datasets—0
Discrete InfoMax Codes for Meta-Learning—0
Semi-Supervised Few-Shot Learning with a Controlled Degree of Task-Adaptive Conditioning—0
Meta-RCNN: Meta Learning for Few-Shot Object Detection—0
Meta-Learning for Variational Inference—0
NORML: Nodal Optimization for Recurrent Meta-Learning—0
Efficient meta reinforcement learning via meta goal generation—0
Meta Learning via Learned Loss—0
Few-Shot Regression via Learning Sparsifying Basis Functions—0
A Data-Efficient Mutual Information Neural Estimator for Statistical Dependency Testing—0
Meta-Learning with Network Pruning for Overfitting Reduction—0
Hidden incentives for self-induced distributional shift—0
Meta-Learning Runge-Kutta—0
Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning—0
Role of two learning rates in convergence of model-agnostic meta-learning—0
ES-MAML: Simple Hessian-Free Meta LearningCode0
Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph CompletionCode0
Data Valuation using Reinforcement LearningCode0
Decoder Choice Network for Meta-LearningCode0
A Theoretical Analysis of the Number of Shots in Few-Shot Learning—0
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAMLCode1
Meta-NeighborhoodsCode0
MetalGAN: a Cluster-based Adaptive Training for Few-Shot Adversarial Colorization—0
Stacking Models for Nearly Optimal Link Prediction in Complex NetworksCode1
Meta Reinforcement Learning for Sim-to-real Domain Adaptation—0
Learning to Tune XGBoost with XGBoost—0
Torchmeta: A Meta-Learning library for PyTorchCode0
Meta-Learning for Few-Shot Time Series Classification—0
Differentially Private Meta-Learning—0
Neural Semantic Parsing in Low-Resource Settings with Back-Translation and Meta-Learning—0
Modular Meta-Learning with Shrinkage—0
Nonstationary Nonparametric Online Learning: Balancing Dynamic Regret and Model Parsimony—0
Cellular neuromodulation in artificial networks—0
Recognizing Variables from their Data via Deep Embeddings of Distributions—0
Learning to Propagate for Graph Meta-LearningCode0
Domain-Agnostic Few-Shot Classification by Learning Disparate Modulators—0
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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