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 1701–1750 of 3569 papers

TitleStatusHype
Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners—0
Dynamic Loss For Robust LearningCode0
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms—0
Environmental Sensor Placement with Convolutional Gaussian Neural ProcessesCode0
Audio Anti-spoofing Using a Simple Attention Module and Joint Optimization Based on Additive Angular Margin Loss and Meta-learning—0
Latent Bottlenecked Attentive Neural ProcessesCode0
Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directions—0
Few-Shot Inductive Learning on Temporal Knowledge Graphs using Concept-Aware Information—0
Meta-Learning of Neural State-Space Models Using Data From Similar Systems—0
Towards Generalization on Real Domain for Single Image Dehazing via Meta-Learning—0
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice—0
Few-shot Metric Learning: Online Adaptation of Embedding for Retrieval—0
Cross-Platform and Cross-Domain Abusive Language Detection with Supervised Contrastive Learning—0
Stackelberg Meta-Learning Based Control for Guided Cooperative LQG Systems—0
Few-shot Classification with Hypersphere Modeling of Prototypes—0
Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-MindCode0
Learning advisor networks for noisy image classificationCode0
MetaLoc: Learning to Learn Wireless Localization—0
Enabling Deep Learning-based Physical-layer Secret Key Generation for FDD-OFDM Systems in Multi-Environments—0
Deep meta-learning for the selection of accurate ultrasound based breast mass classifier—0
HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks—0
Meta-PDE: Learning to Solve PDEs Quickly Without a Mesh—0
Robust Few-shot Learning Without Using any Adversarial SamplesCode0
Faster Adaptive Momentum-Based Federated Methods for Distributed Composition Optimization—0
Deep Multimodal Fusion for Generalizable Person Re-identificationCode0
Fast Adaptive Federated Bilevel Optimization—0
Meta-Learning for Unsupervised Outlier Detection with Optimal Transport—0
A Meta-GNN approach to personalized seizure detection and classification—0
Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach—0
Learning New Tasks from a Few Examples with Soft-Label PrototypesCode0
Data-Efficient Cross-Lingual Transfer with Language-Specific Subnetworks—0
A new benchmark for group distribution shifts in hand grasp regression for object manipulation. Can meta-learning raise the bar?Code0
Few-Shot Classification of Skin Lesions from Dermoscopic Images by Meta-Learning Representative EmbeddingsCode0
RESUS: Warm-Up Cold Users via Meta-Learning Residual User Preferences in CTR PredictionCode0
SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for prior-informed assessment of muscle function and pathology—0
Meta-Learning Initializations for Interactive Medical Image Registration—0
Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking—0
Which is the best model for my data?—0
Imputation of missing values in multi-view data—0
Multi-Environment based Meta-Learning with CSI Fingerprints for Radio Based Positioning—0
Auxiliary task discovery through generate-and-test—0
Learning to Augment via Implicit Differentiation for Domain Generalization—0
UTILIZING FEDERATED LEARNING AND META LEARNING FOR FEW-SHOT LEARNING ON EDGE DEVICES—0
Leveraging Open Data and Task Augmentation to Automated Behavioral Coding of Psychotherapy Conversations in Low-Resource Scenarios—0
A Meta-Learning Based Gradient Descent Algorithm for MU-MIMO Beamforming—0
MARS: Meta-Learning as Score Matching in the Function SpaceCode0
Self-Configuring nnU-Nets Detect Clouds in Satellite Images—0
Federated Learning and Meta Learning: Approaches, Applications, and Directions—0
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks—0
MetaEMS: A Meta Reinforcement Learning-based Control Framework for Building Energy Management System—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