Case Studies in Bayesian Statistics and Machine Learning Workshop Conference Travel; October 2009, Pittsburgh, PA

第一次贝叶斯统计和机器学习研讨会将于2009年10月15日至17日在卡内基梅隆大学举行，将听取以下案例研究的扩展讨论：“使用全基因组阵列进行结直肠癌分子表征和分层的决策理论贝叶斯非参数推断”，由Christopher C. Holmes, Christopher Yau， Ian Tomlinson和Jean-Baptiste Cazier；伊恩·弗农、理查德·鲍尔和迈克尔·戈尔茨坦的《校准宇宙：银河系模拟的贝叶斯不确定性分析》；“基于贝叶斯推断的小角度中子散射数据集的严格误差分析”，作者：Chip Hogg， Jay Kadane， Jong Soo Lee和Sara Majetich。一个新的研究者会议，一个关于贝叶斯分析和机器学习的短期课程介绍，一个关于如何获得资助的会议，以及一个交流会，都旨在吸引学生和最近的毕业生。该基金支持演讲者和年轻研究人员参加将于2009年10月15日至17日在卡内基梅隆大学举行的贝叶斯统计和机器学习第一研讨会的旅行和当地费用。贝叶斯统计和机器学习领域开始共同发展；我们希望讲习班将通过集中注意这些方法的严肃科学应用来加速这一进程。

The First Workshop in Bayesian Statistics and Machine Learning, to be held at Carnegie Mellon University, October 15-17, 2009, will hear extended discussion of the following case studies: "Decision theoretic Bayesian nonparametric inference for the molecular characterization and stratification of colorectal cancer using genome-wide arrays", by Christopher C. Holmes, Christopher Yau, Ian Tomlinson and Jean-Baptiste Cazier; "Calibrating the Universe: A Bayesian Uncertainty Analysis of Galaxy Simulation" by Ian Vernon, Richard Bower and Michael Goldstein; "Rigorous Error Analysis for Small Angle Neutron Scattering Datasets Using Bayesian Inference", by Chip Hogg, Jay Kadane, Jong Soo Lee, and Sara Majetich. A new investigator's session, a short-course introduction to Bayesian analysis and machine learning, a session on how to get a grant, and a mixer, are all aimed at attracting students and recent graduates. This grant supports travel and local expenses for speakers and young investigators to attend the First Workshop in Bayesian Statistics and Machine Learning, to be held at Carnegie Mellon University, October 15-17, 2009. The fields of Bayesian statistics and machine learning are starting to grow together; we hope that the workshop will accelerate this process by focusing attention on serious scientific applications of the methods.