Alexander Gray – författare

Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, engage with the different methods, and adapt them to their own fields of interest.An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.Fully revised and expandedDescribes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data setsFeatures real-world data sets from astronomical surveysUses a freely available Python codebase throughoutIdeal for graduate students, advanced undergraduates, and working astronomers

Since 1981, the British National Conferences on Databases (BNCOD) have p- vided a forum for database researchers to report the latest progress and explore new ideas. Over the last 28 years, BNCOD has evolved from a predominantly national conference into one that is truly international, attracting research c- tributions from all over the world. This volume contains the proceedings of BNCOD 2008. We received 45 s- missions from 22 countries. Each paper was reviewed by three referees, and 14 full papers and 7 posters were accepted. All the research papers and posters are included in this volume, and they are organized into ?ve sections: data mining and privacy, data integration, stream and event data processing, query proce- ing and optimization, and posters. The keynote was delivered by Monica Marinucci, EMEA Programme Dir- tor for Oracle in R&D. She has been involved in various advanced developments concerning Oracle, and participated in EC-funded projects as an expert, es- cially the CHALLENGERS special support action to propose the future of grid computing. In her keynote presentation,she addressedthe audience on the topic of the power of data, emphasizing that the ability to store, handle, manipulate, distribute and replicate data and information can provide a tremendous asset to organizations. She also explored some of the latest directions and developments in the database ?eld, and described how Oracle contributes to them partnering up with other leading organizations in di?erent sectors.