IPAM/Statistics Graduate Workshop

IPAM/统计学研究生研讨会

• 批准号: 0743835
• 负责人: Alan Yuille
• 金额: $ 9.92万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-15 至 2008-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0743835&HistoricalAwards=false
• 关键词: IPAM; Statistics; Graduate; Workshop

The proposed workshop, 'Probabilistic Models of Cognition: The Mathematics of Mind,' will bring together leaders from cognitive science, computer science, mathematics, and statistics who are interested in developing a common mathematical framework for all aspects of cognition, and review how it explains empirical phenomena such as vision, memory, reasoning, learning, planning, and language. This program is motivated by recent advances which offer the promise of modeling human cognition mathematically. The workshop will entail presentations by leading faculty-level lecturers and an audience of graduate students, postdoctoral researchers, and more senior researchers interested in focusing their efforts on probabilistic models of cognition and their applications. Attendees will represent a number of disciplines, including cognitive science, neuroscience, computer science, mathematics, physics, statistics, engineering, and education. Researchers interested in education should be equipped with a wide range of new computational, mathematical and statistical tools that can be used to improve educational technology, curriculum design and assessment, through the development of qualitatively more powerful models of human learning. Researchers in all of these fields, as well as basic cognitive-science researchers, should benefit immensely from interacting with each other and learning about this new generation of cognitive modeling approaches in an unprecedented interdisciplinary environment, with both basic and applied research themes represented among the lectures and discussions.

拟议的研讨会，“认知的概率模型：心灵的数学”将汇集来自认知科学，计算机科学，数学和统计学的领导者，他们有兴趣为认知的各个方面开发一个通用的数学框架，并回顾它如何解释视觉，记忆，推理，学习，规划和语言等经验现象。该计划的动机是最近的进展，提供了数学建模人类认知的承诺。该研讨会将需要由领先的学院级讲师和研究生，博士后研究人员，以及有兴趣专注于认知概率模型及其应用的高级研究人员的观众介绍。与会者将代表多个学科，包括认知科学，神经科学，计算机科学，数学，物理，统计，工程和教育。对教育感兴趣的研究人员应配备广泛的新的计算、数学和统计工具，通过开发质量更强大的人类学习模型，这些工具可用于改进教育技术、课程设计和评估。所有这些领域的研究人员，以及基础认知科学研究人员，应该从相互交流中受益匪浅，并在前所未有的跨学科环境中学习新一代认知建模方法，讲座和讨论中代表了基础和应用研究主题。