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[1]
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Jochen Garcke and Markus Hegland.
Fitting multidimensional data using gradient penalties and the sparse
grid combination technique.
Computing, 84(1-2):1-25, April 2009.
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[2]
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Gregory Beylkin, Jochen Garcke, and Martin J. Mohlenkamp.
Multivariate regression and machine learning with sums of separable
functions.
SIAM Journal on Scientific Computing, 31(3):1840-1857, 2009.
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[3]
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M. Hegland, J. Garcke, and V. Challis.
The combination technique and some generalisations.
Linear Algebra and its Applications, 420(2-3):249-275, 2007.
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[4]
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J. Garcke, M. Hegland, and O. Nielsen.
Parallelisation of sparse grids for large scale data analysis.
ANZIAM Journal, 48(1):11-22, 2006.
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[5]
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J. Garcke and M. Griebel.
Classification with sparse grids using simplicial basis functions.
Intelligent Data Analysis, 6(6):483-502, 2002.
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[6]
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J. Garcke, M. Griebel, and M. Thess.
Data mining with sparse grids.
Computing, 67(3):225-253, 2001.
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[7]
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J. Garcke and M. Griebel.
On the computation of the eigenproblems of hydrogen and helium in
strong magnetic and electric fields with the sparse grid combination
technique.
Journal of Computational Physics, 165(2):694-716, 2000.
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[1]
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J. Garcke.
Classification with sums of separable functions.
In José Balcázar, Francesco Bonchi, Aristides Gionis, and
Michèle Sebag, editors, ECML PKDD 2010, Part I, volume 6321 of
LNAI, pages 458-473, 2010.
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[2]
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S. Börm and J. Garcke.
Approximating gaussian processes with H2-matrices.
In Joost N. Kok, Jacek Koronacki, Ramon Lopez de Mantaras, Stan
Matwin, Dunja Mladen, and Andrzej Skowron, editors, Proceedings of 18th
European Conference on Machine Learning, Warsaw, Poland, September 17-21,
2007. ECML 2007, volume 4701, pages 42-53, 2007.
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[3]
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Jochen Garcke.
Regression with the optimised combination technique.
In W. Cohen and A. Moore, editors, Proceedings of the 23rd ICML
'06, pages 321-328, New York, NY, USA, 2006. ACM Press.
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[4]
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J. Garcke and M. Griebel.
Data mining with sparse grids using simplicial basis functions.
In F. Provost and R. Srikant, editors, Proceedings of the
Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data
Mining, San Francisco, USA, pages 87-96, 2001.
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[1]
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Markus Hegland and Jochen Garcke.
On the numerical solution of the chemical master equation with sums
of rank one tensors.
In W. McLean and A. J. Roberts, editors, Proceedings of the 15th
Biennial Computational Techniques and Applications Conference, CTAC-2010,
volume 52 of ANZIAM J., pages C628-C643, August 2011.
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[2]
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Jochen Garcke.
A dimension adaptive sparse grid combination technique for
regression.
2011.
accepted.
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[3]
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J. Garcke, T. Gerstner, and M. Griebel.
Intraday foreign exchange rate forecasting using sparse grids.
2010.
submitted, also available as INS Preprint No. 1006.
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[4]
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Jochen Garcke, Michael Griebel, and Michael Thess.
Data mining for the category management in the retail market.
In Martin Grötschel, Klaus Lucas, and Volker Mehrmann, editors,
Production Factor Mathematics, pages 81-92. Springer Berlin
Heidelberg, 2010.
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[5]
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J. Garcke.
Sparse grid tutorial.
,
2008.
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[6]
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Jochen Garcke.
An optimised sparse grid combination technique for eigenproblems.
In Proceedings of ICIAM 2007, volume 7 of PAMM, pages
1022301-1022302, 2008.
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[7]
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J. Garcke, M. Griebel, and M. Thess.
Data-Mining für die Angebotsoptimierung im Handel.
In M. Grötschel, K. Lucas, and V. Mehrmann, editors,
Produktionsfaktor Mathematik, acatech diskutiert, pages 111-123. Springer,
2008.
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[8]
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Jochen Garcke and Markus Hegland.
Fitting multidimensional data using gradient penalties and
combination techniques.
In H.G. Bock, E. Kostina, X.P. Hoang, and R. Rannacher, editors,
Proceedings of HPSC 2006, Hanoi, Vietnam, pages 235-248, 2008.
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Abstract ]
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[9]
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Jochen Garcke.
A dimension adaptive sparse grid combination technique for machine
learning.
In Wayne Read, Jay W. Larson, and A. J. Roberts, editors,
Proceedings of the 13th Biennial Computational Techniques and Applications
Conference, CTAC-2006, volume 48 of ANZIAM J., pages C725-C740, 2007.
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[10]
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Jochen Garcke and Michael Griebel.
Semi-supervised learning with sparse grids.
In Massih-Reza Amini, Olivier Chapelle, and Rayid Ghani, editors,
Proceedings of ICML, Workshop on Learning with Partially Classified
Training Data, pages 19-28, 2005.
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[11]
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J. Garcke, M. Hegland, and O. Nielsen.
Parallelisation of sparse grids for large scale data analysis.
In P. Sloot, D. Abramson, A. Bogdanov, J. Dongarra, A. Zomaya, and
Y. Gorbachev, editors, Proceedings of the International Conference on
Computational Science 2003 (ICCS 2003) Melbourne, Australia, volume 2659 of
Lecture Notes in Computer Science, pages 683-692. Springer, 2003.
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[12]
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J. Garcke and M. Griebel.
On the parallelization of the sparse grid approach for data mining.
In S. Margenov, J. Wasniewski, and P. Yalamov, editors,
Large-Scale Scientific Computations, Third International Conference, LSSC
2001, Sozopol, Bulgaria, volume 2179 of Lecture Notes in Computer
Science, pages 22-32. Springer, 2001.
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