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Special Issues on Information-Based Induction Sciences and Machine Learning

机译:基于信息的归纳科学和机器学习的特殊问题

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The Institute of Electronics, Information and Communication Engineers (IEICE) Transactions on Information and Systems announces a forthcoming special issued on "Information-Based Induction Sciences and Machine Learning" to be published in October 2011.rnRecently, a huge mount of data becomes readily available through the internet and various sensors, and machine learning technology for finding underlying rules and acquiring useful knowledge gathers considerable attention. From the theoretical side, machine learning has close connection to basic science such as information theory, statistics, computer science, and statistical physics. Thus, fundamental theory of machine learning is expected to be further developed through interdisciplinary collaboration. On the other hand, from the application side, machine learning technology plays an important role in various fields including signal processing, natural language processing, speech processing, image processing, biology, robot control, financial engineering, and data mining. These application areas possess high potential for real-world industry, and will be further expanded by sharing common methodological challenges.
机译:电子,信息和通信工程师协会(IEICE)的信息和系统交易宣布了即将于2011年10月发布的有关“基于信息的归纳科学和机器学习”的特别刊物。通过互联网和各种传感器,以及用于查找基本规则和获取有用知识的机器学习技术引起了极大的关注。从理论上讲,机器学习与基础科学(例如信息论,统计学,计算机科学和统计物理学)紧密相关。因此,机器学习的基础理论有望通过跨学科的合作得到进一步发展。另一方面,从应用程序的角度来看,机器学习技术在各个领域都发挥着重要作用,包括信号处理,自然语言处理,语音处理,图像处理,生物学,机器人控制,金融工程和数据挖掘。这些应用领域在现实世界中具有很高的潜力,并且将通过共享共同的方法挑战来进一步扩展。

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    《IEICE Transactions on Information and Systems》 |2010年第7期|P.2025-2025|共1页
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  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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  • 入库时间 2022-08-18 00:27:01

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