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 2801–2850 of 3569 papers

TitleStatusHype
Bayesian Online Meta-Learning—0
Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms—0
Provably Faster Algorithms for Bilevel Optimization and Applications to Meta-Learning—0
Learning to Adapt Multi-View Stereo by Self-Supervision—0
Domain Generalization via Semi-supervised Meta LearningCode0
Complementary Meta-Reinforcement Learning for Fault-Adaptive Control—0
A Primal-Dual Subgradient Approachfor Fair Meta LearningCode0
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
Feed-Forward On-Edge Fine-tuning Using Static Synthetic Gradient Modules—0
Adaptive Meta-Learning for Identification of Rover-Terrain DynamicsCode0
Learning Soft Labels via Meta Learning—0
Hidden Incentives for Auto-Induced Distributional Shift—0
GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement 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
Using Sensory Time-cue to enable Unsupervised Multimodal Meta-learning—0
SML: Semantic Meta-learning for Few-shot Semantic Segmentation—0
Teaching to Learn: Sequential Teaching of Agents with Inner States—0
A Markov Decision Process Approach to Active Meta Learning—0
Meta-learning based Alternating Minimization Algorithm for Non-convex OptimizationCode0
Proxy Network for Few Shot LearningCode0
Information Theoretic Meta Learning with Gaussian Processes—0
A Survey on Machine Learning from Few Samples—0
Sparse Meta Networks for Sequential Adaptation and its Application to Adaptive Language Modelling—0
Select-ProtoNet: Learning to Select for Few-Shot Disease Subtype Prediction—0
Yet Meta Learning Can Adapt Fast, It Can Also Break Easily—0
A Preliminary Study on Using Meta-learning Technique for Information Retrieval—0
Multimodal Aggregation Approach for Memory Vision-Voice Indoor Navigation with Meta-Learning—0
A Preliminary Study on Leveraging Meta Learning Technique for Code-switching Speech Recognition—0
A Meta-Learning Control Algorithm with Provable Finite-Time Guarantees—0
Short-term Traffic Prediction with Deep Neural Networks: A Survey—0
MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation—0
learn2learn: A Library for Meta-Learning ResearchCode0
Meta-Learning with Shared Amortized Variational InferenceCode0
Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework—0
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning—0
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization—0
Learning to Learn in a Semi-Supervised Fashion—0
Learning to Profile: User Meta-Profile Network for Few-Shot Learning—0
Query Twice: Dual Mixture Attention Meta Learning for Video Summarization—0
Adaptive Hierarchical Hyper-gradient Descent—0
Meta Learning MPC using Finite-Dimensional Gaussian Process Approximations—0
Topic Adaptation and Prototype Encoding for Few-Shot Visual Storytelling—0
Meta Feature Modulator for Long-tailed Recognition—0
Future Trends for Human-AI Collaboration: A Comprehensive Taxonomy of AI/AGI Using Multiple Intelligences and Learning Styles—0
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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