GREAT Workshop on Astrostatistics and Data Mining in Astronomical Databases

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New statistical techniques for the processing of astronomical data: time series, images, low number statistics for high energy photons, heteroskedastic data, non-detections... Challenges in the data mining of astronomical databases: the class imbalance in training sets or how to define priors robust preprocessing for supervised/unsupervised classification robust inference with heterogeneous datasets, or how to combine (wildly different) observations, models, priors, etc in a training/test set error propagation The challenge of petabyte size databases: scalability, parallel computing, accuracy.Geometric data organization, sky indexing for efficient data retrieval, intelligent access to petabyte size databases Knowledge Discovery in astronomical archives: outlier detection, new object types, parametric inference, model fitting and model selection, etc. Combining the classical domain knowledge approach with machine learning techniques. Global approaches for global datasets. The Galaxy zoo and the Universe zoo. The Virtual Observatories, Data Mining and Astrostatistics: software, standards, protocols...