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Meta-Learning
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Meta-learning is a methodology considered with "learning to learn" machine learning algorithms.
<span style="color:grey; opacity: 0.6">( Image credit: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SQL-o1: Automatic Text-to-SQL Program Synthesis via Self-Reward Heuristic Search
point2vec for Self-Supervised Representation Learning on Point Clouds
GLAD: Generalizable Tuning for Vision-Language Models
CLID-MU: Cross-Layer Information Divergence Based Meta Update Strategy for Learning with Noisy Labels
Imbalanced Regression Pipeline Recommendation
Are encoders able to learn landmarkers for warm-starting of Hyperparameter Optimization?
Mixture of Experts in Large Language Models
Iceberg: Enhancing HLS Modeling with Synthetic Data
Meta-Reinforcement Learning for Fast and Data-Efficient Spectrum Allocation in Dynamic Wireless Networks
Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection
The Bayesian Approach to Continual Learning: An Overview
CHOMET: Conditional Handovers via Meta-Learning
A statistical physics framework for optimal learning
Doodle Your Keypoints: Sketch-Based Few-Shot Keypoint Detection
An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis
Integrated Structural Prompt Learning for Vision-Language Models
Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport
Meta-Learning Transformers to Improve In-Context Generalization
Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning
Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures
ViRefSAM: Visual Reference-Guided Segment Anything Model for Remote Sensing Segmentation
MC-INR: Efficient Encoding of Multivariate Scientific Simulation Data using Meta-Learning and Clustered Implicit Neural Representations
High-Order Deep Meta-Learning with Category-Theoretic Interpretation
Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models
Can Gradient Descent Simulate Prompting?
Dynamic Context-Aware Prompt Recommendation for Domain-Specific AI Applications
Ancient Script Image Recognition and Processing: A Review
FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting
Tailored Conversations beyond LLMs: A RL-Based Dialogue Manager
DIP: Unsupervised Dense In-Context Post-training of Visual Representations
Distributionally robust minimization in meta-learning for system identification
Self-supervised Feature Extraction for Enhanced Ball Detection on Soccer Robots
Universal Music Representations? Evaluating Foundation Models on World Music Corpora
Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training
MetaQAP -- A Meta-Learning Approach for Quality-Aware Pretraining in Image Quality Assessment
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