University of Arkansas Spring Lecture Series in the Mathematical Sciences 2019 and 2020

阿肯色州春季系列讲座2019年和2020年的大学将在费耶特维尔，AR，在2019年4月18日至20日和2020年4月16日至18日，分别在“贝叶斯分析多变量动态系统”和“离散随机结构和预测贝叶斯非参数”的主题。这两个系列讲座的共同主题是如何在贝叶斯统计推断的灵活范例中使用复杂模型来利用数据的力量。在每个系列讲座中，该领域的一位杰出研究人员将就会议主题进行五次讲座，从介绍性讲座开始，并达到当前研究的界限。此外，会议所涵盖领域的十位领军人物将进行一小时的研究报告，并将举行专门的会议，以提供演讲和海报展示。研究生，最近的博士和新的研究人员都得到了这个奖项的支持。为了促进研究生过渡到将在讲座中处理的高级研究课题，将有一个介绍性的研讨会，专门针对他们，在会议开始前一天的下午。2019年的会议将集中在贝叶斯方法建模和高维多变量时间序列的分析与统计分析，结构评估，监测和预报。 重点将是讨论锚定的解耦/再耦合概念及其隐含的战略，提供了一个强大的平台，缩放连贯的统计分析日益复杂的动态系统的实例化状态空间模型的最新进展。基于这一概念的最先进的贝叶斯建模方法，以及它们在许多不同领域的广泛应用，包括金融和商业预测，社会经济，工程和自然科学将在讲座中涵盖。 2020年会议将概述贝叶斯非参数学的最新发展，特别关注离散随机结构，这些结构是许多现代推理目标的关键工具，如主题建模，变点分析或荟萃分析。特别注意将给予最有前途的研究方向，如部分交换和依赖非参数先验，跨越国家的最先进的工具在这一领域。与会者将受益于充分的机会，以建立和促进合作和思想交流，以及暴露在方法和跨学科领域的开放研究问题。关于这些会议的更多细节可在www.example.com上获得https://fulbright.uark.edu/departments/math/research/spring-lecture-series/index.phpThis奖项反映了NSF的法定使命，并被认为值得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来支持。

The University of Arkansas Spring Lecture Series 2019 and 2020 will be held in Fayetteville, AR, on April 18-20, 2019 and April 16-18, 2020, on the topics of "Bayesian Analysis for Multivariate Dynamic Systems" and "Discrete Random Structures and Prediction in Bayesian Nonparametrics," respectively. The common theme of the two Lecture Series is how to harness the power of data using complex models within the flexible paradigm of Bayesian statistical inference. In each Lecture Series, a prominent researcher in the field will give five lectures on the topic of the conference, starting with an introductory one and reaching the boundaries of current research. Additionally, ten leading figures in the area covered by the conference will give one-hour research presentations, and there will be sessions devoted to contributed talks and poster presentations. Graduate students, recent PhDs, and new researchers are supported by this award. To facilitate the transition of graduate students to the advanced research topics that will be treated in the lectures, there will be an introductory workshop, specifically aimed at them, in the afternoon of the day before the conference begins.The 2019 conference will focus on Bayesian approaches to modeling and analysis of high-dimensional multivariate time series with a broad purview over problems of statistical analysis, structure assessment, monitoring and forecasting. Emphasis will be given on discussion of recent advances in state-space models anchored on instantiations of the decouple/recouple concept and its implied strategies that provide a powerful platform for scaling coherent statistical analysis to increasingly complex dynamic systems. State-of-the-art Bayesian modeling approaches based on this concept, as well as their broad range of applications in many different areas including financial and commercial forecasting, socio-economic, engineering and natural sciences will be covered in the lectures. The 2020 conference will give an overview of recent developments in Bayesian nonparametrics, specifically focusing on discrete random structures that are key tools for many modern inferential goals, such as topic modeling, change-point analyses or meta-analysis. Special attention will be given to the most promising research directions such as partial exchangeability and dependent nonparametric priors, spanning state-of-the-art tools in this area. The attendees will benefit from ample opportunities to forge and foster collaborations and exchange of ideas as well as exposure to open research problems in methodological and cross-disciplinary domains. More details on these conferences are available at https://fulbright.uark.edu/departments/math/research/spring-lecture-series/index.phpThis 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.