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 901–950 of 3569 papers

TitleStatusHype
Benchmarking and Improving Compositional Generalization of Multi-aspect Controllable Text GenerationCode0
Meta-Learning for Stochastic Gradient MCMCCode0
Deep Task-Based Analog-to-Digital ConversionCode0
Meta-learning how to Share Credit among Macro-ActionsCode0
Adaptive Fine-Grained Sketch-Based Image RetrievalCode0
Learning to Demodulate from Few Pilots via Offline and Online Meta-LearningCode0
Algorithm Selection on a Meta LevelCode0
Efficient time stepping for numerical integration using reinforcement learningCode0
Meta-Learning of Structured Task Distributions in Humans and MachinesCode0
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution TasksCode0
Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learningCode0
Learning Task-Aware Energy Disaggregation: a Federated ApproachCode0
Meta-Learning Priors for Efficient Online Bayesian RegressionCode0
Meta-Learning Probabilistic Inference For PredictionCode0
Learning to adapt: a meta-learning approach for speaker adaptationCode0
Deep Multimodal Fusion for Generalizable Person Re-identificationCode0
Zero-shot task adaptation by homoiconic meta-mappingCode0
Learning New Tasks from a Few Examples with Soft-Label PrototypesCode0
Learning Low-Dimensional Embeddings for Black-Box OptimizationCode0
Learning Invariances for Policy GeneralizationCode0
Learning Generalized Zero-Shot Learners for Open-Domain Image GeolocalizationCode0
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial AttacksCode0
Attentional Meta-learners for Few-shot Polythetic ClassificationCode0
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal PredictionCode0
Meta-Learning Parameterized SkillsCode0
Image Deformation Meta-Networks for One-Shot LearningCode0
Learning How to Demodulate from Few Pilots via Meta-LearningCode0
Learning One-Shot Imitation from Humans without HumansCode0
Deep Learning Theory Review: An Optimal Control and Dynamical Systems PerspectiveCode0
Learning Deep Morphological Networks with Neural Architecture SearchCode0
Learning advisor networks for noisy image classificationCode0
Learning an Explicit Hyperparameter Prediction Function Conditioned on TasksCode0
Deep Compressed SensingCode0
Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance EstimationCode0
Learning Fast Adaptation with Meta Strategy OptimizationCode0
Leaping Through Time with Gradient-based Adaptation for RecommendationCode0
learn2learn: A Library for Meta-Learning ResearchCode0
Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal ResourcesCode0
A Meta-Transfer Objective for Learning to Disentangle Causal MechanismsCode0
Layer-compensated Pruning for Resource-constrained Convolutional Neural NetworksCode0
An Ensemble of Epoch-wise Empirical Bayes for Few-shot LearningCode0
Decomposed Meta-Learning for Few-Shot Sequence LabelingCode0
Decoder Choice Network for Meta-LearningCode0
Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based TrainingCode0
Episodic Multi-Task Learning with Heterogeneous Neural ProcessesCode0
E-QUARTIC: Energy Efficient Edge Ensemble of Convolutional Neural Networks for Resource-Optimized LearningCode0
Deciphering Trajectory-Aided LLM Reasoning: An Optimization PerspectiveCode0
Asynchronous Distributed Bilevel OptimizationCode0
Capability-Aware Shared Hypernetworks for Flexible Heterogeneous Multi-Robot CoordinationCode0
Learning to Continually Learn Rapidly from Few and Noisy DataCode0
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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