An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning

25 Nov 2016Guoqiang ZhongLi-Na WangJunyu Dong

Since about 100 years ago, to learn the intrinsic structure of data, many representation learning approaches have been proposed, including both linear ones and nonlinear ones, supervised ones and unsupervised ones. Particularly, deep architectures are widely applied for representation learning in recent years, and have delivered top results in many tasks, such as image classification, object detection and speech recognition... (read more)

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