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Document type:
IDP-Arbeit 
Author(s):
Dmitrij Boschko 
Title:
Generalization and Parallelization of Sherman-Morrison System Matrix Updates for Sparse Grid Density Estimation 
Abstract:
Sherman-Morrison rank-one updates have been used successfully for adaptive sparse grid density estimation. This allowed for regularization and adaptivity, but until now, this has only been possible in the offline/online splitting context using an orthogonal decomposition, such as tridiagonal. The new approach studied in this paper generalizes the old version of the Sherman-Morrison formula based sparse grid density estimation by using the Sherman-Morrison-Woodbury (SMW) formula. This allows for...    »
 
Keywords:
Data Mining; Sparse Grids; SG++ 
Supervisor:
Bungartz, Hans-Joachim 
Advisor:
Röhner, Kilian; Obersteiner, Michael 
Year:
2019 
Quarter:
4. Quartal 
Year / month:
2019-11 
Month:
Nov 
Language:
en 
University:
Technical University of Munich 
Faculty:
Fakultät für Mathematik