Workshop Proposal: Machine Learning and Discovery Science

研讨会提案：机器学习和发现科学

• 批准号: 1744019
• 负责人: Aram Galstyan
• 金额: $ 5万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2018-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1744019&HistoricalAwards=false
• 关键词: Workshop; Proposal; Machine; Learning; Discovery

The emergence of big data has been transformational in many areas in science and engineering - biology, health sciences, material science, physics, and so on. At the heart of this transformation is statistical machine learning, a subfield of computer science that aims at studying and developing algorithms that can analyze large volumes of data. The goal of this international workshop is to bring together researchers, both from USA and Armenia, who work on machine learning (ML) and other scientific disciplines that are poised to benefit from the recent advances in ML. The workshop will include participation from leading experts in a number of disciplines. In machine learning, the workshop will cover topics such as deep learning, tensor methods, unsupervised learning with high dimensional data, and so on. In computational social sciences, the topics will include social network analysis, behavioral modeling, modeling of socio-technical systems. And in computational biology, the topics will cover gene expression analysis, computational neuroscience, predictive diagnostics. The workshop will serve as a bridge to get these communities talking to one another and explore collaborative research. The workshop will provide a forum for the participating researchers to formulate a research agenda that will help to utilize recent advances in ML in data-intensive disciplines. Second, the workshop will support participation of senior graduate students and early career scientists. Finally, the workshop will promote scientific cooperation between the American and Armenian researchers.This award is cofunded by the Office of International Science and Engineering.

大数据的出现在许多科学和工程领域带来了变革--生物学、健康科学、材料科学、物理学等等。这种变革的核心是统计机器学习，这是计算机科学的一个分支，旨在研究和开发能够分析大量数据的算法。这个国际研讨会的目标是汇集来自美国和亚美尼亚的研究人员，他们致力于机器学习（ML）和其他有望从ML最新进展中受益的科学学科。 研讨会将邀请若干学科的主要专家参加。在机器学习方面，研讨会将涵盖深度学习、张量方法、高维数据无监督学习等主题;在计算社会科学方面，研讨会将涵盖社会网络分析、行为建模、社会技术系统建模等主题。在计算生物学方面，主题将涵盖基因表达分析，计算神经科学，预测诊断。该研讨会将作为一个桥梁，让这些社区相互交谈，探索合作研究。 该研讨会将为参与研究人员提供一个论坛，以制定一个研究议程，这将有助于在数据密集型学科中利用ML的最新进展。第二，研讨会将支持高年级研究生和早期职业科学家的参与。最后，讲习班将促进美国和亚美尼亚研究人员之间的科学合作，该奖项由国际科学和工程办公室共同资助。