Review of Small Data Learning Methods
2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC)(2018)
摘要
Machine learning algorithms are widely applied in the fields such as Machine Vision, Natural Language Processing, Image Processing and Automatic Speech Recognition. Deep learning based on mass data has achieved success in many application, for example, Alpha Go. However, learning from small data remains a key challenge in machine learning. This paper introduces the basic ideas of the small data learning theory, present the main machine learning algorithms and analyze their major characteristics. The paper also summarizes the current research trends.
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关键词
Machine-Learning,Small-Data,SVM,KNN,Bootstrap,Bayesian-Methods
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