ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2013, Vol. 50 ›› Issue (9): 1799-1804.

所属专题: 2013人工智能进展

• 综述 •    下一篇


余 凯 贾 磊 陈雨强 徐 伟   

  1. (百度 北京 100085) (
  • 出版日期: 2013-09-15

Deep Learning: Yesterday, Today, and Tomorrow

Yu Kai, Jia Lei, Chen Yuqiang, and Xu Wei   

  1. (Baidu, Beijing 100085)
  • Online: 2013-09-15

摘要: 机器学习是人工智能领域的一个重要学科.自从20世纪80年代以来,机器学习在算法、理论和应用等方面都获得巨大成功.2006年以来,机器学习领域中一个叫“深度学习”的课题开始受到学术界广泛关注,到今天已经成为互联网大数据和人工智能的一个热潮.深度学习通过建立类似于人脑的分层模型结构,对输入数据逐级提取从底层到高层的特征,从而能很好地建立从底层信号到高层语义的映射关系.近年来,谷歌、微软、IBM、百度等拥有大数据的高科技公司相继投入大量资源进行深度学习技术研发,在语音、图像、自然语言、在线广告等领域取得显著进展.从对实际应用的贡献来说,深度学习可能是机器学习领域最近这十年来最成功的研究方向.将对深度学习发展的过去和现在做一个全景式的介绍,并讨论深度学习所面临的挑战,以及将来的可能方向.

关键词: 机器学习, 深度学习, 语音识别, 图像识别, 自然语言处理, 在线广告

Abstract: Machine learning is an important area of artificial intelligence. Since 1980s, huge success has been achieved in terms of algorithms, theory, and applications. From 2006, a new machine learning paradigm, named deep learning, has been popular in the research community, and has become a huge wave of technology trend for big data and artificial intelligence. Deep learning simulates the hierarchical structure of human brain, processing data from lower level to higher level, and gradually composing more and more semantic concepts. In recent years, Google, Microsoft, IBM, and Baidu have invested a lot of resources into the R&D of deep learning, making significant progresses on speech recognition, image understanding, natural language processing, and online advertising. In terms of the contribution to real-world applications, deep learning is perhaps the most successful progress made by the machine learning community in the last 10 years. In this article, we will give a high-level overview about the past and current stage of deep learning, discuss the main challenges, and share our views on the future development of deep learning.

Key words: machine learning, deep learning, speech recognition, image recognition, natural language processing, online advertising