TOPICS TO BE COVERED:
Computer science:
• numerical linear algebra;
• iterative solvers;
• optimization techniques;
• massive data management;
• hybrid programming, heterogeneous computer architectures;
• high level languages;
Statistics, signal processing, ...
• random fields;
• non-gaussian and gaussian processes;
• Markovian and non-Markovian processes and sampling techniques;
• Independent Component Analyses;
• wavelet transforms;
• compressive sensing;
• massive data sets mining;
Data analysis
• novel tools and techniques for and recent progress in:
• power spectrum estimation;
• non-Gaussianity detection and characterization;
• lensing reconstruction;
• component separation;
• map making;
• time domain processing;
