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 2601–2650 of 3569 papers

TitleStatusHype
Dif-MAML: Decentralized Multi-Agent Meta-Learning—0
CURI: A Benchmark for Productive Concept Learning Under UncertaintyCode1
Meta-Learning of Structured Task Distributions in Humans and MachinesCode0
MetaPhys: Few-Shot Adaptation for Non-Contact Physiological MeasurementCode1
Improving Few-Shot Learning through Multi-task Representation Learning TheoryCode0
Dialogue Generation on Infrequent Sentence Functions via Structured Meta-Learning—0
Exploration in Approximate Hyper-State Space for Meta Reinforcement LearningCode1
Fast Few-Shot Classification by Few-Iteration Meta-LearningCode0
Bayesian Meta-reinforcement Learning for Traffic Signal Control—0
MetaMix: Improved Meta-Learning with Interpolation-based Consistency Regularization—0
Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations—0
Bayesian Online Meta-Learning—0
Provably Faster Algorithms for Bilevel Optimization and Applications to Meta-Learning—0
Non-greedy Gradient-based Hyperparameter Optimization Over Long Horizons—0
Improving Few-Shot Visual Classification with Unlabelled Examples—0
Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms—0
Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift—0
Interventional Few-Shot LearningCode1
Learning to Adapt Multi-View Stereo by Self-Supervision—0
BOML: A Modularized Bilevel Optimization Library in Python for Meta LearningCode1
A Primal-Dual Subgradient Approachfor Fair Meta LearningCode0
Domain Generalization via Semi-supervised Meta LearningCode0
Complementary Meta-Reinforcement Learning for Fault-Adaptive Control—0
A Meta-learning based Distribution System Load Forecasting Model Selection Framework—0
Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey—0
Attribute Propagation Network for Graph Zero-shot Learning—0
Unfairness Discovery and Prevention For Few-Shot Regression—0
Fair Meta-Learning For Few-Shot Classification—0
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time—0
Automating Outlier Detection via Meta-LearningCode1
Adaptive Meta-Learning for Identification of Rover-Terrain DynamicsCode0
Feed-Forward On-Edge Fine-tuning Using Static Synthetic Gradient Modules—0
Learning Soft Labels via Meta Learning—0
Hidden Incentives for Auto-Induced Distributional Shift—0
Few-Shot Unsupervised Continual Learning through Meta-ExamplesCode1
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification TasksCode1
GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning—0
Using Sensory Time-cue to enable Unsupervised Multimodal Meta-learning—0
An Extensive Experimental Evaluation of Automated Machine Learning Methods for Recommending Classification Algorithms (Extended Version)—0
Efficient Quantum State Sample Tomography with Basis-dependent Neural-networks—0
SML: Semantic Meta-learning for Few-shot Semantic Segmentation—0
Teaching to Learn: Sequential Teaching of Agents with Inner States—0
Few-shot Learning with LSSVM Base Learner and Transductive ModulesCode1
Meta Learning for Few-Shot One-class ClassificationCode1
Transfer Graph Neural Networks for Pandemic ForecastingCode1
A Markov Decision Process Approach to Active Meta Learning—0
Meta-Learning with Sparse Experience Replay for Lifelong Language LearningCode1
Prototype Completion with Primitive Knowledge for Few-Shot LearningCode1
Meta-learning based Alternating Minimization Algorithm for Non-convex OptimizationCode0
Proxy Network for Few Shot LearningCode0
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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