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 2151–2200 of 3569 papers

TitleStatusHype
DAMSL: Domain Agnostic Meta Score-based LearningCode0
Meta-Learning with Variational Semantic Memory for Word Sense DisambiguationCode0
Signal Transformer: Complex-valued Attention and Meta-Learning for Signal Recognition—0
Write like you: Synthesizing your cursive online Chinese handwriting via metric-based meta learningCode1
Meta-Learning with Fewer Tasks through Task InterpolationCode1
Light Field Networks: Neural Scene Representations with Single-Evaluation RenderingCode1
Minimax and Neyman-Pearson Meta-Learning for Outlier LanguagesCode0
Rotom: A Meta-Learned Data Augmentation Framework for Entity Matching, Data Cleaning, Text Classification, and BeyondCode1
Learning to Learn Semantic Factors in Heterogeneous Image Classification—0
Modality-specific Distillation—0
Méta-apprentissage : classification de messages en catégories émotionnelles inconnues en entraînement (Meta-learning : Classifying Messages into Unseen Emotional Categories)—0
Variance-reduced First-order Meta-learning for Natural Language Processing Tasks—0
DReCa: A General Task Augmentation Strategy for Few-Shot Natural Language Inference—0
Information-Theoretic Analysis of Epistemic Uncertainty in Bayesian Meta-learning—0
Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and AdvertisingCode1
Meta-HAR: Federated Representation Learning for Human Activity RecognitionCode1
Efficient and Modular Implicit DifferentiationCode2
BaMBNet: A Blur-aware Multi-branch Network for Defocus DeblurringCode1
Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent—0
Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning—0
Short-Term Stock Price-Trend Prediction Using Meta-Learning—0
Towards mental time travel: a hierarchical memory for reinforcement learning agentsCode1
ProtAugment: Unsupervised diverse short-texts paraphrasing for intent detection meta-learningCode1
Multiple Domain Experts Collaborative Learning: Multi-Source Domain Generalization For Person Re-Identification—0
Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images—0
Learning Generative Prior with Latent Space Sparsity Constraints—0
Federated Meta Learning Enhanced Acoustic Radio Cooperative Framework for Ocean of Things Underwater Acoustic Communications—0
MIASSR: An Approach for Medical Image Arbitrary Scale Super-ResolutionCode1
Auxiliary learning induced graph convolutional networks—0
Meta Reinforcement Learning for Fast Adaptation of Hierarchical Policies—0
Fast Training Method for Stochastic Compositional Optimization Problems—0
Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks—0
Discovering Weight Initializers with Meta LearningCode0
Meta Learning the Step Size in Policy Gradient Methods—0
Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection—0
Minimum-Delay Adaptation in Non-Stationary Reinforcement Learning via Online High-Confidence Change-Point DetectionCode1
Bag of Tricks for Long-Tailed Visual Recognition with Deep Convolutional Neural NetworksCode1
Multiple Meta-model Quantifying for Medical Visual Question AnsweringCode1
Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate PredictionCode1
Exploiting Adapters for Cross-lingual Low-resource Speech RecognitionCode0
Fast and Slow Learning of Recurrent Independent Mechanisms—0
DRILL: Dynamic Representations for Imbalanced Lifelong LearningCode0
Sample Efficient Linear Meta-Learning by Alternating Minimization—0
Deep Metric Learning for Few-Shot Image Classification: A Review of Recent Developments—0
HetMAML: Task-Heterogeneous Model-Agnostic Meta-Learning for Few-Shot Learning Across Modalities—0
Meta-Inductive Node Classification across Graphs—0
Meta Auxiliary Learning for Facial Action Unit Detection—0
Exploring the Similarity of Representations in Model-Agnostic Meta-LearningCode0
Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users—0
AutoDebias: Learning to Debias for RecommendationCode1
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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