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 251–300 of 3569 papers

TitleStatusHype
Task-Specific Gradient Adaptation for Few-Shot One-Class Classification—0
M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference—0
A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded SmoothnessCode0
Transformer-Based Contrastive Meta-Learning For Low-Resource Generalizable Activity Recognition—0
Imitation Learning from Suboptimal Demonstrations via Meta-Learning An Action RankerCode0
Meta-Learning-Based Delayless Subband Adaptive Filter using Complex Self-Attention for Active Noise Control—0
EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIsCode1
Personalized Dynamic Music Emotion Recognition with Dual-Scale Attention-Based Meta-LearningCode1
Automatic Self-supervised Learning for Social Recommendations—0
Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain GeneralizationCode0
Learning to Adapt to Low-Resource Paraphrase Generation—0
A Meta-Learning Approach to Bayesian Causal DiscoveryCode0
Consistency of Compositional Generalization across Multiple LevelsCode0
MetaRuleGPT: Recursive Numerical Reasoning of Language Models Trained with Simple Rules—0
Spatio-Temporal Fuzzy-oriented Multi-Modal Meta-Learning for Fine-grained Emotion RecognitionCode0
TSEML: A task-specific embedding-based method for few-shot classification of cancer molecular subtypesCode0
Reservoir Computing for Fast, Simplified Reinforcement Learning on Memory Tasks—0
Learning from Noisy Labels via Self-Taught On-the-Fly Meta Loss Rescaling—0
Generalizable Representation Learning for fMRI-based Neurological Disorder IdentificationCode0
Memory-Reduced Meta-Learning with Guaranteed Convergence—0
LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification—0
Meta Curvature-Aware Minimization for Domain Generalization—0
ViSymRe: Vision-guided Multimodal Symbolic Regression—0
Label-template based Few-Shot Text Classification with Contrastive Learning—0
Three-in-One: Robust Enhanced Universal Transferable Anti-Facial Retrieval in Online Social Networks—0
Neural Networks for Threshold Dynamics ReconstructionCode0
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image SegmentationCode2
ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement LearningCode0
SeFENet: Robust Deep Homography Estimation via Semantic-Driven Feature Enhancement—0
Efficient Task Grouping Through Samplewise Optimisation Landscape Analysis—0
The broader spectrum of in-context learning—0
FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systems—0
Model-Agnostic Meta-Learning for Fault Diagnosis of Induction Motors in Data-Scarce Environments with Varying Operating Conditions and Electric Drive Noise—0
Task-driven Image Fusion with Learnable Fusion Loss—0
Efficient Model Compression Techniques with FishLeg—0
Reinforcement learning to learn quantum states for Heisenberg scaling accuracyCode0
Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAsCode1
Towards Cross-Lingual Audio Abuse Detection in Low-Resource Settings with Few-Shot LearningCode0
Learn to Unlearn: Meta-Learning-Based Knowledge Graph Embedding Unlearning—0
Meta-learning Loss Functions of Parametric Partial Differential Equations Using Physics-Informed Neural Networks—0
QUOTA: Quantifying Objects with Text-to-Image Models for Any Domain—0
MetaGraphLoc: A Graph-based Meta-learning Scheme for Indoor Localization via Sensor Fusion—0
On the ERM Principle in Meta-Learning—0
MetaCropFollow: Few-Shot Adaptation with Meta-Learning for Under-Canopy Navigation—0
Material synthesis through simulations guided by machine learning: a position paper—0
AdaptAgent: Adapting Multimodal Web Agents with Few-Shot Learning from Human Demonstrations—0
MLDGG: Meta-Learning for Domain Generalization on Graphs—0
Online Item Cold-Start Recommendation with Popularity-Aware Meta-LearningCode0
Effective Predictive Modeling for Emergency Department Visits and Evaluating Exogenous Variables Impact: Using Explainable Meta-learning Gradient Boosting—0
AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with TransformersCode2
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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