Deep Learning and Its Applications to Signal and Information Processing

被引:334
作者
Yu, Dong [1 ]
Deng, Li [1 ]
机构
[1] Microsoft Res, Redmond, WA USA
关键词
D O I
10.1109/MSP.2010.939038
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
Today, signal processing research has a significantly widened its scope compared with just a few years ago [4], and machine learning has been an important technical area of the signal processing society. Since 2006, deep learninga new area of machine learning research has emerged [7], impacting a wide range of signal and information processing work within the traditional and the new, widened scopes. Various workshops, such as the 2009 ICML Workshop on Learning Feature Hierarchies; the 2008 NIPS Deep Learning Workshop: Foundations and Future Directions; and the 2009 NIPS Workshop on Deep Learning for Speech Recognition and Related Applications as well as an upcoming special issue on deep learning for speech and language processing in IEEE Transactions on Audio, Speech, and Language Processing (2010) have been devoted exclusively to deep learning and its applications to classical signal processing areas. We have also seen the government sponsor research on deep learning (e.g., the DARPA deep learning program, available at http://www.darpa.mil/ipto/solicit/baa/BAA-09-40- PIP.pdf). © 2010 IEEE.
引用
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页码:145 / +
页数:6
相关论文
共 15 条
[1]  
[Anonymous], 2009, NIPS WORKSH DEEP LEA
[2]  
[Anonymous], P ICML
[3]  
[Anonymous], P SIGIR WORKSH INF R
[4]  
[Anonymous], P INT C DOC AN REC I
[5]  
[Anonymous], P NIPS
[6]  
[Anonymous], 2010, 2010003 U TOR
[7]   Learning Deep Architectures for AI [J].
Bengio, Yoshua .
FOUNDATIONS AND TRENDS IN MACHINE LEARNING, 2009, 2 (01) :1-127
[8]  
Deng L., 2010, P INT
[9]   Expanding the scope of signal processing [J].
Deng, Li .
IEEE SIGNAL PROCESSING MAGAZINE, 2008, 25 (03) :2-+
[10]  
Deselaers T., 2009, P 4 WORKSH STAT MACH, P233, DOI DOI 10.1016/J.POLYMDEGRADSTAB.2006.08.025