A Brief Survey of Associations Between Meta-Learning and General AI
This paper briefly reviews the history of meta-learning and describes its contribution to general AI. Meta-learning improves model generalization capacity and devises general algorithms applicable to both in-distribution and out-of-distribution tasks potentially. General AI replaces task-specific models with general algorithmic systems introducing higher level of automation in solving diverse tasks using AI. We summarize main contributions of meta-learning to the developments in general AI, including memory module, meta-learner, coevolution, curiosity, forgetting and AI-generating algorithm. We present connections between meta-learning and general AI and discuss how meta-learning can be used to formulate general AI algorithms.
Code (0)
등록된 구현이 없습니다.
Tasks
Meta-LearningSimilar Papers 제목 키워드 기반
A Brief Summary of Interactions Between Meta-Learning and Self-Supervised Learning
This paper briefly reviews the connections between meta-learning and self-supervised learning. Meta-learning can be applied to improve model generalization capability and to construct general AI algorithms. Self-supervis…
Data AugmentationMeta-LearningSelf-Supervised LearningUnsupervised Pre-trainingMeta-learning approaches for few-shot learning: A survey of recent advances
Despite its astounding success in learning deeper multi-dimensional data, the performance of deep learning declines on new unseen tasks mainly due to its focus on same-distribution prediction. Moreover, deep learning is …
Deep LearningFew-Shot LearningMeta-LearningA Comprehensive Overview and Survey of Recent Advances in Meta-Learning
This article reviews meta-learning also known as learning-to-learn which seeks rapid and accurate model adaptation to unseen tasks with applications in highly automated AI, few-shot learning, natural language processing …
BIG-bench Machine LearningDeep LearningFew-Shot LearningImage Classification+2Higher serum 25(OH)D concentration is associated with lower risk of metabolic syndrome among Aboriginal and Torres Strait Islander peoples in Australia
Although previous observational studies have shown associations between serum 25-hydroxyvitamin D (25(OH)D) concentration and metabolic syndrome, this association has not yet been investigated among Aboriginal and Torres…
Exploring Graph Classification Techniques Under Low Data Constraints: A Comprehensive Study
This survey paper presents a brief overview of recent research on graph data augmentation and few-shot learning. It covers various techniques for graph data augmentation, including node and edge perturbation, graph coars…
Data AugmentationFew-Shot LearningGraph ClassificationGraph Generation+2