Conference on Statistical Learning and Data Science

哥伦比亚大学将于2018年6月4日至6日在纽约市举办为期三天的统计学习与数据科学/非参数统计会议。会议的目的是将来自学术界、工业界和政府的统计学习、数据科学和非参数统计方面的研究人员聚集在一起。统计机器学习被广泛认为是一个非常活跃的跨学科研究领域，与统计学、优化和计算机科学密切相关。此外，它还在数据科学和大数据等新的重要领域发挥着至关重要的作用。由于技术的进步，“大数据时代”的海量、复杂数据几乎遍及现代科学研究的各个方面。管理如此庞大的数据，并做出可靠的预测和推断是至关重要的。统计机器学习技术在处理此类数据方面具有很大的灵活性，在不同的科学学科中有着广泛的应用。本次会议预计将(1)汇集来自不同学科的研究人员，包括统计学、计算机科学、机器学习、工程、生物医学和其他相关研究领域，以解决统计学习、数据科学和非参数统计的最新发展和新问题；(2)促进研究人员之间的互动和合作；(3)讨论统计学习和数据科学的新思路和未来研究方向。专注于科学和工程领域的知识发现，(4)为初级研究人员提供了一个与该领域的顶尖科学家互动和学习的绝佳机会。会议将包括三次全体会议、55次邀请会议和海报会议。会议主题包括无监督、半监督和监督学习，以及在排名、文本和网络挖掘、网络分析、生物信息学、高维数据、功能数据、基因组学、药物发现、入侵和欺诈检测方面的应用。美国国家科学基金会将为学生、博士后学者和早期职业研究人员提供旅行支持，以鼓励他们参加本次活动。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，认为值得支持。

Columbia University will host a three-day conference on Statistical Learning and Data Science/Nonparametric Statistics, June 4-6, 2018 in New York City. The objective of the conference is to bring together researchers in statistical learning, data science and nonparametric statistics from academia, industry, and government. Statistical machine learning is widely recognized as a very active area of interdisciplinary research, closely related to statistics, optimization, and computer science. In addition, it also plays an essential role in the new important areas of data science and big data. Due to advances in technology, massive and complex data in the "big data era" are prevalent in almost every aspect of modern scientific research. It is critical to manage such huge amounts of data, and make reliable prediction and inference. Statistical machine learning techniques have developed substantial flexibility in handling such data, with a wide range of applications in diverse scientific disciplines. This conference is expected to (1) bring together researchers from different disciplines, including statistics, computer science, machine learning, engineering, and biomedical and other related research fields, to address recent development and emerging issues in statistical learning, data science and nonparametric statistics, (2) promote interactions and collaborations among researchers, (3) discuss new ideas and future research directions for statistical learning and data science, with a focus towards knowledge discovery in sciences and engineering, (4) provide an excellent opportunity for junior researchers to interact and learn from leading scientists in the field. The conference will consist of three plenary sessions, 55 invited sessions and poster sessions. Conference topics include unsupervised, semi-supervised and supervised learning, with applications in rankings, text and web mining, network analysis, bioinformatics, high-dimensional data, functional data, genomics, drug discovery, intrusion and fraud detection. NSF funding will provide travel support to students, post-doctoral scholars, and early-career researchers to encourage their participation in this event. The conference website is https://publish.illinois.edu/sldsc2018/.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.