Symposium on Machine Learning for Anomaly Detection

该奖项支持2004年5月22日至23日在斯坦福大学举行的为期两天的异常检测机器学习研讨会的参与者。研讨会的目的是将来自不同应用领域的研究人员、学生和工业从业者聚集在一起，让他们报告他们最近的成果并讨论共同关注的问题。研讨会的一个核心方面是由知名研究人员进行的11次邀请演讲，他们的工作提供了使用机器学习方法检测各种领域异常的良好研究样本。通过向与会者展示来自其他领域的想法，鼓励互动和协作，并帮助确定共同的开放问题，研讨会促进了异常检测方面的改进研究。传播计划包括建立一个网站（http://cll.stanford.edu/symposia/anomaly/），上面有演讲者的演讲和相关论文可供下载，准备一份研讨会报告，并组织一个专门的期刊，专门讨论异常检测的机器学习方法。最后，研讨会将有助于提高对异常检测方法的理解，异常检测方法在公共卫生监测、计算机网络安全和会计欺诈检测等许多领域变得越来越重要。

This award supports participants in a two-day symposium on machine learning for anomaly detection to be held at Stanford University on May 22-23, 2004. The purpose of the symposium is to bring together researchers, students, and industrial practitioners from different application areas and let them report their recent results and discuss common concerns. A central aspect of the symposium are eleven invited talks given by established researchers whose work provides a good sampling of research using machine learning methods to detect anomalies across a variety of domains. The symposium fosters improved research in anomaly detection by exposing attendees to ideas from other fields, encouraging interaction and collaboration, and helping to identify common open problems. Dissemination plans include developing a website (http://cll.stanford.edu/symposia/anomaly/) with the speakers talks and relevant papers available for download, preparing a workshop report, and organizing a special journal issue devoted to machine learning approaches to anomaly detection. Finally, the symposium will contribute to increased understanding of methods for anomaly detection, which is becoming important in many areas such as public health monitoring, computer network security, and accounting fraud detection.