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

第一届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，将听取对以下案例研究的深入讨论：“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理”，作者：Christopher C. Holmes、Christopher Yau、Ian Tomlinson 和 Jean-Baptiste Cazier； “校准宇宙：星系模拟的贝叶斯不确定性分析”，作者：Ian Vernon、Richard Bower 和 Michael Goldstein； “使用贝叶斯推理对小角中子散射数据集进行严格误差分析”，作者：Chip Hogg、Jay Kadane、Jong Soo Lee 和 Sara Majetich。新研究者的课程、贝叶斯分析和机器学习的短期课程介绍、如何获得资助的课程以及混合课程，都是为了吸引学生和应届毕业生。 该赠款支持演讲者和年轻研究者参加将于 2009 年 10 月 15 日至 17 日在卡内基梅隆大学举办的第一届贝叶斯统计和机器学习研讨会的旅费和当地费用。贝叶斯统计和机器学习领域开始共同发展；我们希望讲习班将重点放在这些方法的认真科学应用上，从而加速这一进程。

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.