I/UCRC: University of Florida Planning Grant: I/UCRC for Big Learning

该项目建议建立NSF I/UCR大学习中心(CBL)。CBL的使命是通过CBL联盟的统一和协调努力，在大规模深度学习算法、系统和应用方面开创先河。CBL的愿景是为智能驱动的社会创造智能使能器。随着自然系统、工程系统和人类活动产生的爆炸性大数据，我们需要智能算法和系统来帮助我们进行大规模自动提取洞察力的决策。在我们的社会迈向充满机会的智能世界之际，拟议的CBL中心是一项及时的倡议。CBL联盟有望成为深度学习研究和应用的磁石，并吸引领先的研究人员、热情的企业家、IT和行业巨头共同努力，完成这一充满希望的使命和愿景。这笔规划赠款将导致成功地提议建立NSF I/UCR大学习中心，并在多个校区和大量行业合作伙伴之间建立一个坚实的财团。CBL有以下更广泛的影响。(1)在开创性研究和应用方面对深度学习社区做出重大贡献和影响，以应对广泛的现实世界挑战。(2)对推广工业界的产品和服务，特别是我们会员的产品和服务作出重大贡献和影响。(3)为我们迫切需要的下一代人才的教育做出重大贡献和影响，这些人才来自真实世界的背景和来自学术界和产业界的世界级导师。(4)我们的会议、论坛、会议和计划中的培训课程将极大地促进和拓宽数字图书馆的研究和实体化。拟议的项目旨在建立NSF I/UCR大学习中心(CBL)。随着多种形式的挑战(如图像、视频、语音、文本和问答)的戏剧性突破，机器智能的复兴正在迫在眉睫。CBL的使命是通过CBL联盟的统一和协调努力，通过融合我们大量教职员工、学生和行业合作伙伴的广泛专业知识，在大规模深度学习(DL)算法、系统和应用方面开创先河。CBL的愿景是为智能驱动的社会创造智能使能器。CBL在以下关键研究主题方面具有开创性的智力价值。(1)算法新颖。本文主要介绍了深度结构、复杂深度神经网络、脑启发组件、优化、深度强化学习和无监督学习等新的深度学习算法和体系结构。(2)制度创新。我们提出了新颖的架构、资源管理和软件框架，用于在桌面、移动、集群和云上实现大规模数字图书馆平台和应用。(3)在健康、移动/物联网和监控方面的新应用。在规划阶段，我们将建立坚实的中心战略规划、营销计划，以及由四个学术站点和大量行业成员组成的CBL联合体。CBL有以下更广泛的影响。(1)在开创性研究和应用方面对深度学习社区做出重大贡献和影响，以应对广泛的现实世界挑战。(2)对推广工业界的产品和服务，特别是我们会员的产品和服务作出重大贡献和影响。(3)为我们迫切需要的下一代人才的教育做出重大贡献和影响，这些人才来自真实世界的背景和来自学术界和产业界的世界级导师。(4)我们的会议、论坛、会议和计划中的培训课程将极大地促进和拓宽数字图书馆的研究和实体化。

This project proposes to establish the NSF I/UCR Center for Big Learning (CBL). The mission of CBL is to pioneer in large-scale deep learning algorithms, systems, and applications through unified and coordinated efforts in the CBL consortium. The vision of CBL is to create intelligence enablers towards intelligence-driven society. With the explosive big data generated from natural systems, engineered systems, and human activities, we need intelligent algorithms and systems to facilitate our decision making with distilled insights automatically at scale. The proposed CBL center is a timely initiative as our society moves towards intelligence-enabled world of opportunities. The CBL consortium is expected to become the magnet of deep learning research and applications and attract leading researchers, enthusiastic entrepreneurs, IT and industry giants working together on accomplishing the promising mission and vision. This planning grant will lead to a successful proposal for the establishment of the NSF I/UCR Center for Big Learning with a solid consortium across multiple campuses and a large number of industry partners. CBL has the following broader impacts. (1) Making significant contributions and impacts to the deep learning community on pioneering research and applications to address a broad spectrum of real-world challenges. (2) Making significant contributions and impacts to promote products and services of industry in general and our members in particular. (3) Making significant contributions and impacts to the urgently-needed education of our next-generation talents with real-world settings and world-class mentors from both academia and industry. (4) Our meetings, forums, conferences, and planned training sessions will greatly promote and broaden the research and materialization of DL. The proposed project aims to establish the NSF I/UCR Center for Big Learning (CBL). With dramatic breakthroughs in multiple modalities of challenges (e.g., image, video, speech, text, and Q&A), the renaissance of machine intelligence is looming.The mission of CBL is to pioneer in large-scale deep learning (DL) algorithms, systems, and applications through unified and coordinated efforts in the CBL consortium via fusion of broad expertise from our large number of faculty members, students, and industry partners. The vision of CBL is to create intelligence enablers towards intelligence-driven society. CBL possesses the pioneering intellectual merit in the following key research themes. (1) Novel algorithms. This theme focuses on novel DL algorithms and architectures, such as deep architecture, complex deep neural networks, brain-inspired components, optimization, deep reinforcement learning, and unsupervised learning. (2) Novel systems. We propose novel architectures, resource management, and software frameworks for enabling large-scale DL platforms and applications on desktops, mobiles, clusters, and clouds. (3) Novel applications in health, mobile/IoT, and surveillance. During the planning phase, we will establish a solid center strategic plan, marketing plan, and the CBL consortium that consists of four academic sites and a large number of industrial members. CBL has the following broader impacts. (1) Making significant contributions and impacts to the deep learning community on pioneering research and applications to address a broad spectrum of real-world challenges. (2) Making significant contributions and impacts to promote products and services of industry in general and our members in particular. (3) Making significant contributions and impacts to the urgently-needed education of our next-generation talents with real-world settings and world-class mentors from both academia and industry. (4) Our meetings, forums, conferences, and planned training sessions will greatly promote and broaden the research and materialization of DL.