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 3001–3050 of 3569 papers

TitleStatusHype
Improving Few-shot Learning by Spatially-aware Matching and CrossTransformer—0
From Learning to Meta-Learning: Reduced Training Overhead and Complexity for Communication SystemsCode1
Automated Relational Meta-learningCode1
DAWSON: A Domain Adaptive Few Shot Generation Framework—0
Few-shot Relation Extraction via Bayesian Meta-learning on Task Graphs—0
Meta Variance Transfer: Learning to Augment from the Others—0
On the Iteration Complexity of Hypergradient Computations—0
Learning Attentive Meta-Transfer—0
Deep Transfer Learning Based Downlink Channel Prediction for FDD Massive MIMO SystemsCode0
Variational Metric Scaling for Metric-Based Meta-LearningCode0
Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Data—0
Meta-Learning PAC-Bayes Priors in Model Averaging—0
AutoML: Exploration v.s. ExploitationCode0
Meta-Graph: Few Shot Link Prediction via Meta LearningCode0
TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning—0
Continuous Meta-Learning without TasksCode0
Meta-Learned Per-Instance Algorithm Selection in Scholarly Recommender Systems—0
Semantic Regularization: Improve Few-shot Image Classification by Reducing Meta Shift—0
A Broader Study of Cross-Domain Few-Shot LearningCode1
Meta-Learning Initializations for Image SegmentationCode0
Conditional Super Learner—0
Associative Alignment for Few-shot Image ClassificationCode0
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population—0
Meta-Learning without MemorizationCode0
Unsupervised Curricula for Visual Meta-Reinforcement Learning—0
Improved Few-Shot Visual Classification—0
MetalGAN: Multi-Domain Label-Less Image Synthesis Using cGANs and Meta-Learning—0
MetaFun: Meta-Learning with Iterative Functional UpdatesCode0
Learning to Recommend via Meta Parameter Partition—0
BADGER: Learning to (Learn [Learning Algorithms] through Multi-Agent Communication)Code0
MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification—0
Online-Within-Online Meta-LearningCode0
MetaInit: Initializing learning by learning to initialize—0
Learning to Learn By Self-CritiqueCode0
Efficient Meta Learning via Minibatch Proximal Update—0
VIABLE: Fast Adaptation via Backpropagating Learned Loss—0
Sparsely Grouped Input Variables for Neural NetworksCode0
Ranking architectures using meta-learning—0
Real-Time Object Tracking via Meta-Learning: Efficient Model Adaptation and One-Shot Channel Pruning—0
Learning to Learn Words from Visual ScenesCode0
Regularized Fine-grained Meta Face Anti-spoofingCode0
Meta-Learning of Neural Architectures for Few-Shot LearningCode1
Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning—0
Differentiable Meta-learning Model for Few-shot Semantic Segmentation—0
Investigating Active Learning and Meta-Learning for Iterative Peptide Design—0
Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online—0
Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means FeaturesCode0
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual RecognitionCode0
Six Degree-of-Freedom Body-Fixed Hovering over Unmapped Asteroids via LIDAR Altimetry and Reinforcement Meta-Learning—0
Self-Supervised Learning For Few-Shot Image ClassificationCode0
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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