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83 Publications visible to you, out of a total of 83

Abstract (Expand)

Nowadays astronomical catalogs contain patterns of hundreds of millions of objects with data volumes in the terabyte range. Upcoming projects will gather such patterns for several billions of objects with peta- and exabytes of data. From a machine learning point of view, these settings often yield unsupervised, semi-supervised, or fully supervised tasks, with large training and huge test sets. Recent studies have demonstrated the effectiveness of prototype-based learning schemes such as simple nearest neighbor models. However, although being among the most computationally efficient methods for such settings (if implemented via spatial data structures), applying these models on all remaining patterns in a given catalog can easily take hours or even days. In this work, we investigate the practical effectiveness of GPU-based approaches to accelerate such nearest neighbor queries in this context. Our experiments indicate that carefully tuned implementations of spatial search structures for such multi-core devices can significantly reduce the practical runtime. This renders the resulting frameworks an important algorithmic tool for current and upcoming data analyses in astronomy.

Authors: Justin Heinermann, Oliver Kramer, Kai Lars Polsterer, Fabian Gieseke

Date Published: 2013

Publication Type: InProceedings

Abstract

Not specified

Authors: Kai Lars Polsterer, Peter-Christian Zinn, Fabian Gieseke

Date Published: 2013

Publication Type: Journal

Abstract (Expand)

The task of estimating an object's redshift based on photometric data is one of the most important ones in astronomy. This is especially the case for quasars. Common approaches for this regression task are based on nearest neighbor search, template fitting schemes, or combinations of, e.g., clustering and regression techniques. As we show in this work, simple frameworks like k-nearest neighbor regression work extremely well if one considers the overall feature space (containing patterns of all objects with low, middle, and high redshifts). However, such methods naturally fail as soon as only very few or even no training patterns are given in the appropriate region of the feature space. In the literature, a wide range of other regression techniques can be found. Among the most popular ones are regularized regression schemes like ridge regression or support vector regression. In this work, we show that an out-of-the-box application of this type of schemes for the whole feature space is difficult due to the involved computational requirements and the specific properties of the data at hand. However, in contrast to nearest neighbor search schemes, such methods can be employed to extrapolate, i.e., they can be used to predict redshifts for patterns in new, unseen regions of the feature space.

Authors: F. Gieseke, Kai L. Polsterer, Peter-Christian Zinn

Date Published: 1st Sep 2012

Publication Type: InProceedings

Abstract

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Authors: R. J. Assef, K. D. Denney, C. S. Kochanek, B. M. Peterson, S. Kozłowski, N. Ageorges, R. S. Barrows, P. Buschkamp, M. Dietrich, E. Falco, C. Feiz, H. Gemperlein, A. Germeroth, C. J. Grier, R. Hofmann, M. Juette, R. Khan, M. Kilic, V. Knierim, W. Laun, R. Lederer, M. Lehmitz, R. Lenzen, U. Mall, K. K. Madsen, H. Mandel, P. Martini, S. Mathur, K. Mogren, P. Mueller, V. Naranjo, A. Pasquali, K. Polsterer, R. W. Pogge, A. Quirrenbach, W. Seifert, D. Stern, B. Shappee, C. Storz, J. Van Saders, P. Weiser, D. Zhang

Date Published: 1st Dec 2011

Publication Type: Journal

Abstract

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Authors: A. Pasquali, A. Bik, S. Zibetti, N. Ageorges, W. Seifert, W. Brandner, H.-W. Rix, M. Jütte, V. Knierim, P. Buschkamp, C. Feiz, H. Gemperlein, A. Germeroth, R. Hofmann, W. Laun, R. Lederer, M. Lehmitz, R. Lenzen, U. Mall, H. Mandel, P. Müller, V. Naranjo, K. Polsterer, A. Quirrenbach, L. Schäffner, C. Storz, P. Weiser

Date Published: 1st Apr 2011

Publication Type: Journal

Abstract

Not specified

Authors: Fabian Gieseke, Kai Lars Polsterer, Andreas Thom, Peter Zinn, Dominik Bomanns, Ralf-Jurgen Dettmar, Oliver Kramer, Jan Vahrenhold

Date Published: 1st Dec 2010

Publication Type: InProceedings

Abstract

Not specified

Authors: Marcus Jütte, Volker Knierim, Kai Polsterer, Michael Lehmitz, Clemens Storz, Walter Seifert, Nancy Ageorges

Date Published: 19th Jul 2010

Publication Type: Journal

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