Deep Learning: Methods and Applications

被引:1543
作者
Deng, Li [1 ]
Yu, Dong [1 ]
机构
[1] Microsoft Res, 1 Microsoft Way, Redmond, WA 98052 USA
来源
FOUNDATIONS AND TRENDS IN SIGNAL PROCESSING | 2013年 / 7卷 / 3-4期
关键词
D O I
10.1561/2000000039
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This monograph provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise or knowledge of the authors; (2) the application areas that have already been transformed by the successful use of deep learning technology, such as speech recognition and computer vision; and (3) the application areas that have the potential to be impacted significantly by deep learning and that have been experiencing research growth, including natural language and text processing, information retrieval, and multimodal information processing empowered by multi-task deep learning.
引用
收藏
页码:I / 387
页数:195
相关论文
共 425 条
[31]   Representation Learning: A Review and New Perspectives [J].
Bengio, Yoshua ;
Courville, Aaron ;
Vincent, Pascal .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (08) :1798-1828
[32]   Learning Deep Architectures for AI [J].
Bengio, Yoshua .
FOUNDATIONS AND TRENDS IN MACHINE LEARNING, 2009, 2 (01) :1-127
[33]  
Bengio Yoshua, 2013, DEEP LEARNING REPRES, V1306, P1091, DOI DOI 10.1007/978-3-642-39593-2_1
[34]  
Bergstra J, 2012, J MACH LEARN RES, V13, P281
[35]   An application of discriminative feature extraction lo filter-bank-based speech recognition [J].
Biem, A ;
Katagiri, S ;
McDermott, E ;
Juang, BH .
IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING, 2001, 9 (02) :96-110
[36]   Graphical model architectures for speech recognition [J].
Bilmes, JA ;
Bartels, C .
IEEE SIGNAL PROCESSING MAGAZINE, 2005, 22 (05) :89-100
[37]   Dynamic Graphical Models An overview [J].
Bilmes, Jeff .
IEEE SIGNAL PROCESSING MAGAZINE, 2010, 27 (06) :29-42
[38]  
Bordes A., 2011, P ASS ADV ART INT AA
[39]  
Bordes A., 2013, MACHINE LEARNING
[40]  
Bottou L., 2004, P NEUR INF PROC SYST