CASE STUDIES IN BAYESIAN STATISTICS AND MACHINE LEARNING

贝叶斯统计和机器学习的案例研究延续了贝叶斯统计案例研究系列研讨会的传统，并于2011年10月14-15日举行了一次会议。统计和计算机科学中通常的会议和讲习班形式强调方法而不是应用，这往往扼杀了有关方法对实质性问题影响的讨论。案例研究讲习班系列的独特形式使人们得以对具体应用问题进行实质性讨论，最重要的是叙述了实质性科学问题如何需要新方法或新的现有方法的应用、研究人员在实际问题中遇到的障碍以及由此产生的解决办法。统计学和机器学习在整个科学中提供了基本的方法，但在传统的会议中，很少强调科学和数据分析问题表达之间的联系。这一研讨会促进了统计学和计算机科学界的思想交流，并促进了在科学调查中面临重大挑战的工作。这些案例研究突出了统计机器学习方法的新应用被用来回答科学问题的方式。研讨会特别支持年轻调查人员的努力，部分原因是包括专门由年轻调查人员介绍的一段时间。

Case Studies in Bayesian Statistics and Machine Learning continues the tradition of the workshop series Case Studies in Bayesian Statistics with a meeting October 14-15, 2011. The usual format for meetings and workshops in statistics and computer science emphasize methods over applications, which often stifles discussion about the impact of the methods on the substantive problem. The unique format of the case studies workshop series has allowed for substantive discussion of application-specific issues, most importantly a narrative of how the substantive scientific problem demanded either new methods or the novel application of existing approaches, the obstacles in the real problem that the researchers encountered, and the solutions that resulted. Statistics and machine learning provide essential methodologies throughout the sciences, yet the connection between the science and the data analytic problem formulation is rarely emphasized in traditional conferences. This workshop fosters cross-pollination of ideas from the statistics and computer science ommunities and promotes work that takes on important challenges in scientific investigation. The case studies highlight the way novel application of statistical machine learning methods are used to answer a scientific question. The workshop especially supports efforts by young investigators, in part by including a session of presentations exclusively by younger investigators.