SHF: Conference: Hardware and Algorithms for Learning On-a-chip; November 5, 2015; Austin, TX

SHF：会议：片上学习的硬件和算法；

• 批准号: 1545974
• 负责人: Yu Cao
• 金额: $ 1.5万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-15 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1545974&HistoricalAwards=false
• 关键词: SHF; Conference; Hardware; Algorithms; Learning

Support for student participation in a workshop to establish a forum for discussion of the current practices, as well as future research needs in three interrelated subareas of brain related sciences is provided through this grant. The three specific subareas that the workshop will discuss are: hardware acceleration of on-chip learning; machine learning algorithms and neuro-inspired information processing; and nano-electronic design for learning, with the focus on performance and energy efficiency. The workshop will consist of three sessions and will be followed by a panel discussion, and will end with a poster session to present student work. The conference will not only provide a venue for researchers to address problems but also a platform for graduate students and others to learn about cutting-edge research by attending invited talks, presentations, tutorials in the general area.The outcome of this workshop include a webpage hosted by the Arizona State University to disseminate the program and discussions, as well as a report that clearly identifies major research challenges and needs in computational neurosciences, machine learning, and hardware design. The papers and posters will be published through the workshop proceedings. These results will illustrate new and exciting inter-disciplinary research problems of interest to the related communities, and articulate a vision of conducting further research in this area. The final workshop report will also be submitted to NSF as an annual report and will be released online for sharing with the research community in general.

支持学生参加讲习班，建立一个论坛，讨论目前的做法，以及未来的研究需要在三个相互关联的子领域的大脑相关的科学是通过这个补助金提供。研讨会将讨论的三个具体子领域是：片上学习的硬件加速;机器学习算法和神经启发的信息处理;以及面向学习的纳米电子设计，重点是性能和能效。研讨会将包括三个会议，并将随后进行小组讨论，并将以海报会议结束，以展示学生的工作。会议不仅为研究人员提供了一个解决问题的场所，也为研究生和其他人提供了一个平台，通过参加邀请的讲座，演讲，一般领域的教程来了解前沿研究。这次研讨会的成果包括由亚利桑那州立大学主办的一个网页，以传播该计划和讨论，以及一份报告，清楚地确定了计算神经科学，机器学习和硬件设计的主要研究挑战和需求。这些论文和海报将通过讲习班的会议记录发表。这些结果将说明新的和令人兴奋的跨学科的研究问题感兴趣的相关社区，并阐明了在这一领域进行进一步研究的愿景。研讨会的最终报告也将作为年度报告提交给NSF，并将在网上发布，供研究界分享。