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学者论坛:Learning Deep Neural Networks from Limited Data
文:人力资源部教师发展中心 来源:计算机学院 党委教师工作部、人力资源部(教师发展中心) 时间:2019-05-15 4078

  人力资源部教师发展中心“学者论坛”活动邀请东京大学Tatsuya Harada(原田逹也)到校交流。具体安排如下,欢迎广大师生参加:

  一、主 题:Learning Deep Neural Networks from Limited Data

  二、主讲人:东京大学 Tatsuya Harada(原田逹也) 教授

  三、时 间:2019年5月17日(星期五)下午14:30

  四、地 点:清水河校区图书馆天韵厅

  五、主持人:计算机科学与工程学院(网络空间安全学院)姬艳丽 副教授

  六、内容简介:

  Training deep neural networks from limited data for constructing an accurate prediction model is one of the crucial tasks in machine learning. In this talk, we introduce unsupervised domain adaptation and learning method using between-class examples as a method to train DNNs from limited supervised data. Besides, we will briefly introduce various topics that we are working on in our team.

  七、主讲人简介

  Tatsuya Harada is a Professor in the Department of Information Science and Technology at the University of Tokyo. His research interests center on visual recognition, machine learning, and intelligent robot. He received his Ph.D. from the University of Tokyo in 2001. He is also a team leader at RIKEN AIP and a vice director of Research Center for Medical Bigdata at National Institute of Informatics, Japan.

  八、主办单位:人力资源部教师发展中心

    承办单位:计算机科学与工程学院(网络空间安全学院)

 

                                                                 人力资源部教师发展中心

                               2019年5月14日


编辑:杨棋凌  / 审核:李果  / 发布:陈伟

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