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 2201–2250 of 3569 papers

TitleStatusHype
SuperCone: Unified User Segmentation over Heterogeneous Experts via Concept Meta-learning—0
Supplementary Meta-Learning: Towards a Dynamic Model for Deep Neural Networks—0
Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation—0
SuSana Distancia is all you need: Enforcing class separability in metric learning via two novel distance-based loss functions for few-shot image classification—0
Symbiotic Message Passing Model for Transfer Learning between Anti-Fungal and Anti-Bacterial Domains—0
Synthetic speech detection using meta-learning with prototypical loss—0
System 2 Reasoning via Generality and Adaptation—0
System-Agnostic Meta-Learning for MDP-based Dynamic Scheduling via Descriptive Policy—0
System Identification via Meta-Learning in Linear Time-Varying Environments—0
Tailored Conversations beyond LLMs: A RL-Based Dialogue Manager—0
Tailored Forecasting from Short Time Series via Meta-learning—0
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time—0
Taming the Herd: Multi-Modal Meta-Learning with a Population of Agents—0
TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition—0
Task-Adaptive Clustering for Semi-Supervised Few-Shot Classification—0
Task-Adaptive Pseudo Labeling for Transductive Meta-Learning—0
Task Agnostic Continual Learning via Meta Learning—0
Task-Agnostic Meta-Learning for Few-shot Learning—0
Task Agnostic Meta-Learning for Few-Shot Learning—0
Task-Agnostic Semantic Communications Relying on Information Bottleneck and Federated Meta-Learning—0
Task Aligned Generative Meta-learning for Zero-shot Learning—0
Task Aligned Meta-learning based Augmented Graph for Cold-Start Recommendation—0
Task Attended Meta-Learning for Few-Shot Learning—0
Task-Aware Meta Learning-based Siamese Neural Network for Classifying Obfuscated Malware—0
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Environmental Systems—0
Task-Aware Part Mining Network for Few-Shot Learning—0
Task Calibration for Distributional Uncertainty in Few-Shot Classification—0
Task Consistent Prototype Learning for Incremental Few-shot Semantic Segmentation—0
Task-Distributionally Robust Data-Free Meta-Learning—0
Task-driven Image Fusion with Learnable Fusion Loss—0
Task Fingerprinting for Meta Learning in Biomedical Image Analysis—0
TaskMix: Data Augmentation for Meta-Learning of Spoken Intent Understanding—0
Task Relatedness-Based Generalization Bounds for Meta Learning—0
Task-similarity Aware Meta-learning through Nonparametric Kernel Regression—0
Task-Specific Gradient Adaptation for Few-Shot One-Class Classification—0
Task Weighting in Meta-learning with Trajectory Optimisation—0
TalaGen: A System for Automatic Tala Identification and Generation—0
Teaching Models to Improve on Tape—0
Teaching to Learn: Sequential Teaching of Agents with Inner States—0
Team Fernando-Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection—0
Teasing Apart Architecture and Initial Weights as Sources of Inductive Bias in Neural Networks—0
Temporal Variational Implicit Neural Representations—0
Terminal Adaptive Guidance for Autonomous Hypersonic Strike Weapons via Reinforcement Learning—0
Test-Time Adaptation for Generalizable Task Progress Estimation—0
Test-Time Adaptation for Point Cloud Upsampling Using Meta-Learning—0
Test-time Adaptation for Real Image Denoising via Meta-transfer Learning—0
Text Emotion Distribution Learning from Small Sample: A Meta-Learning Approach—0
Thalamocortical contribution to solving credit assignment in neural systems—0
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning—0
The Athenian Academy: A Seven-Layer Architecture Model for Multi-Agent Systems—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