Workshop on the Algorithmic, Mathematical, and Statistical Foundations of Data Science

数据科学的算法、数学和统计基础研讨会

• 批准号: 1637436
• 负责人: Xiaoming Huo
• 金额: $ 10万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1637436&HistoricalAwards=false
• 关键词: Workshop; Algorithmic; Mathematical; Statistical; Foundations

A workshop on the Algorithmic, Mathematical, and Statistical Foundations of Data Science will be held April 28-30, 2016 in Arlington, VA. The event will bring together leading researchers in computer science, mathematics, and statistics to address foundational issues related to data science. The objectives of the workshop are three-fold: (i) identify fundamental areas in the emerging discipline of Data Science where collaboration between computer scientists, mathematicians, and statisticians is necessary to achieve significant progress; (ii) Assess how collaboration between computer scientists, mathematicians, and statisticians could potentially contribute to workforce development by advancing and transforming the Data Science research training of Ph.D. students and post-docs; and (iii) Suggest different infrastructure modalities that could significantly promote and advance such collaborations. The main deliverable of the workshop is a white paper that will serve as a guideline for professional societies and funding agencies. The rapid emergence of the Big Data phenomenon presents both opportunities and challenges. While massive data may allow the generation of models and the design of algorithms that have improved inferential power, such models and algorithms may be less successful on modest-sized data sets. The challenge for researchers is to develop theoretical principles that will allow the scaling of inference and learning to massive-scale datasets, and algorithms that control errors even in the presence of heterogeneity in the data generation and data sampling processes. These challenges will require collaborations between researchers representing theoretical computer science, mathematics, statistics, machine learning and data mining, and high performance computing. This award supports a workshop that brings together leaders from these communities of researchers to discuss the challenges and opportunities for collaborative work in this developing field.

关于数据科学的数学，数学和统计基础的研讨会将于2016年4月28日至30日在弗吉尼亚州阿灵顿举行。 该活动将汇集计算机科学，数学和统计学领域的领先研究人员，以解决与数据科学相关的基础问题。 研讨会的目标有三个方面：（i）确定数据科学新兴学科的基本领域，计算机科学家，数学家和统计学家之间的合作是实现重大进展所必需的;（ii）评估计算机科学家，数学家和统计学家之间的合作如何通过推进和转变博士的数据科学研究培训来促进劳动力发展。学生和博士后;和（三）建议不同的基础设施模式，可以大大促进和推动这种合作。 讲习班的主要成果是一份白色文件，将作为专业协会和供资机构的指导方针。 大数据现象的迅速出现带来了机遇和挑战。 虽然海量数据可以允许生成具有改进的推理能力的模型和算法的设计，但是这样的模型和算法在中等大小的数据集上可能不太成功。研究人员面临的挑战是开发理论原则，允许扩展推理和学习以扩展数据集，以及即使在数据生成和数据采样过程中存在异质性的情况下也能控制错误的算法。 这些挑战将需要代表理论计算机科学、数学、统计学、机器学习和数据挖掘以及高性能计算的研究人员之间的合作。该奖项支持一个研讨会，汇集了来自这些研究人员社区的领导人，讨论在这个发展中领域合作的挑战和机遇。