Phase I I/UCRC Carnegie Mellon University: Center for Big Learning CBL

第一阶段 I/UCRC 卡内基梅隆大学：大学习中心 CBL

• 批准号: 1747769
• 负责人: Ruslan Salakhutdinov
• 金额: $ 75万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-02-15 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1747769&HistoricalAwards=false
• 关键词: Phase; UCRC; Carnegie; Mellon; University

This project establishes the Industry/University Cooperative Research Center for Big Learning (CBL). With substantial breakthroughs in deep learning, the renaissance of machine intelligence is unfolding. The vision is to create intelligence towards the intelligence-driven society. Through catalyzing the fusion of diverse expertise from the consortium of faculty members, students, industry partners, and federal agencies, CBL seeks to create state-of-the-art deep learning methodologies and technologies and enable intelligent applications, transforming broad domains, such as business, media, healthcare, Internet-of-Things, and cybersecurity. This timely initiative creates a unique platform for empowering our next-generation talents with real-world relevance and significance.The mission is to pioneer novel deep learning algorithms, intelligent systems, and novel applications through unified and coordinated efforts in the CBL consortium via fusion of broad expertise from our large number of center faculty members, students, industry partners, and government agencies. The Carnegie-Mellon University site will focus on deep learning algorithms and platforms and work with other sites on novel applications.The CBL is expected to have broad transformative impacts in technologies, education, and the society. CBL seeks to create pioneering research and applications to address a broad spectrum of real-world challenges, making significant contributions and impacts to the deep learning community, the industry and the society at large. The discoveries from CBL will make significant contributions to promote products and industrial services in general and CBL industry partners in particular. As the magnet of deep learning research and applications, CBL offers an ideal platform to nurture next-generation talents through world-class mentors from both academia and industry, disseminate the cutting-edge technologies, and facilitate industry/university collaborative research.The center repository will be hosted at http://nsfcbl.org. The data, code, documents will be well organized and maintained on the CBL server for the duration of the center plus five years. The internal code repository will be managed by GitLab. After the software packages are well documented and tested, they will be released and managed by popular public servers, such as GitHub and Bitbucket.

该项目建立了大学习产学合作研究中心（CBL）。随着深度学习的重大突破，机器智能的复兴正在展开。愿景是创造智能，迈向智能驱动的社会。通过促进教师、学生、行业合作伙伴和联邦机构联盟的不同专业知识的融合，CBL 致力于创建最先进的深度学习方法和技术，并实现智能应用，从而改变广泛的领域，例如商业、媒体、医疗保健、物联网和网络安全。这一及时的举措创造了一个独特的平台，为我们的下一代人才赋予现实世界的相关性和意义。其使命是通过 CBL 联盟的统一和协调努力，通过融合来自我们中心众多教职员工、学生、行业合作伙伴和政府机构的广泛专业知识。卡内基梅隆大学网站将专注于深度学习算法和平台，并与其他网站合作开发新颖的应用程序。CBL 预计将在技术、教育和社会方面产生广泛的变革性影响。 CBL 致力于创造开创性的研究和应用来解决广泛的现实挑战，为深度学习社区、行业和整个社会做出重大贡献和影响。 CBL 的发现将为推广产品和工业服务，特别是 CBL 行业合作伙伴做出重大贡献。作为深度学习研究和应用的磁石，CBL提供了一个理想的平台，通过来自学术界和工业界的世界级导师培养下一代人才，传播前沿技术，促进产学研合作。中心资源库将在 http://nsfcbl.org 上托管。在中心存续期间及五年内，数据、代码、文档将在 CBL 服务器上妥善组织和维护。内部代码存储库将由 GitLab 管理。软件包经过充分记录和测试后，将由流行的公共服务器（例如 GitHub 和 Bitbucket）发布和管理。