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Meta-Learning: A Survey - 2018

Meta-Learning: A Survey

Survey Paper on Meta-Learning

Research Area:  Machine Learning

Abstract:

Meta-learning, or learning to learn, is the science of systematically observing how different machine learning approaches perform on a wide range of learning tasks, and then learning from this experience, or meta-data, to learn new tasks much faster than otherwise possible. Not only does this dramatically speed up and improve the design of machine learning pipelines or neural architectures, it also allows us to replace hand-engineered algorithms with novel approaches learned in a data-driven way. In this chapter, we provide an overview of the state of the art in this fascinating and continuously evolving field.

Keywords:  
Meta-Learning
Machine Learning
Deep Learning

Author(s) Name:  Joaquin Vanschoren

Journal name:  Machine Learning

Conferrence name:  

Publisher name:  arXiv:1810.03548

DOI:  https://doi.org/10.48550/arXiv.1810.03548

Volume Information: