Deep Learning: Methods and Applications

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Foundations and TrendsR in Signal ProcessingVol. 7, Nos. 3 4 (2013) 197 387c 2014 L. Deng and D. YuDOI: learning : Methods and ApplicationsLi DengMicrosoft ResearchOne Microsoft WayRedmond, WA 98052; YuMicrosoft ResearchOne Microsoft WayRedmond, WA 98052; Organizationofthismonograph ..............2022 Some Historical Context of Deep Learning2053 Three Classes of Deep learning Athree-waycategorization ................. Deep networks for unsupervised or generative learning . . . Deepnetworksforsupervisedlearning ........... Hybriddeepnetworks ....................2264 Deep Autoencoders Unsupervised Introduction ......................... Use of deep autoencoders to extract speech features . . . Transformingautoencoders .................2395 Pre-Trained Deep Neural Networks A Unsupervisedlayer-wisepre-training.

learning or hierarchical learning, has emerged as a new area of machine learning research [20, 163]. During the past several years, the techniques ... learn distributed and hierarchical feature representations, and to make effective use of both labeled and unlabeled data. Active researchers in this area include those at University of

  Feature, Learning, Hierarchical, Hierarchical features, Hierarchical learning