Improving the performance of photometric regression models via massive parallel feature selection

Kai Lars Polsterer; Fabian Cristian Gieseke; Christian Igel; Tomotsugu Goto

Improving the performance of photometric regression models via massive parallel feature selection

Kai Lars Polsterer, Fabian Cristian Gieseke, Christian Igel, Tomotsugu Goto

Original language	English
Title of host publication	Astronomical Data Analysis Software and Systems XXIII
Editors	N. Manset, P. Forshay
Number of pages	4
Volume	485
Publisher	Astronomical Society of the Pacific
Publication date	2014
Pages	425-428
ISBN (Print)	978-1-58381-854-1
ISBN (Electronic)	978-1-58381-855-8
Publication status	Published - 2014
Event	Astronomical Data Analysis Software and Systems XXIII - Waikoloa Beach Marriott, Hawaii, United States Duration: 29 Sept 2013 → 3 Oct 2013 Conference number: 23

Conference

Conference	Astronomical Data Analysis Software and Systems XXIII
Number	23
Location	Waikoloa Beach Marriott
Country/Territory	United States
City	Hawaii
Period	29/09/2013 → 03/10/2013

Series	Astronomical Society of the Pacific. Conference Proceedings
Volume	485
ISSN	1050-3390

Access to Document

Improving the Performance of Photometric Regression Models via Massive Parallel Feature SelectionFinal published version, 15.3 MB

http://www.aspbooks.org/a/volumes/article_details?paper_id=36266

Cite this

Polsterer, K. L., Gieseke, F. C., Igel, C., & Goto, T. (2014). Improving the performance of photometric regression models via massive parallel feature selection. In N. Manset, & P. Forshay (Eds.), Astronomical Data Analysis Software and Systems XXIII (Vol. 485, pp. 425-428). Astronomical Society of the Pacific. http://www.aspbooks.org/a/volumes/article_details?paper_id=36266

Improving the performance of photometric regression models via massive parallel feature selection. / Polsterer, Kai Lars; Gieseke, Fabian Cristian ; Igel, Christian et al.
Astronomical Data Analysis Software and Systems XXIII. ed. / N. Manset; P. Forshay. Vol. 485 Astronomical Society of the Pacific, 2014. p. 425-428 (Astronomical Society of the Pacific. Conference Proceedings, Vol. 485).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Polsterer, KL, Gieseke, FC , Igel, C & Goto, T 2014, Improving the performance of photometric regression models via massive parallel feature selection. in N Manset & P Forshay (eds), Astronomical Data Analysis Software and Systems XXIII. vol. 485, Astronomical Society of the Pacific, Astronomical Society of the Pacific. Conference Proceedings, vol. 485, pp. 425-428, Astronomical Data Analysis Software and Systems XXIII, Hawaii, United States, 29/09/2013. <http://www.aspbooks.org/a/volumes/article_details?paper_id=36266>

Polsterer, Kai Lars ; Gieseke, Fabian Cristian ; Igel, Christian et al. / Improving the performance of photometric regression models via massive parallel feature selection. Astronomical Data Analysis Software and Systems XXIII. editor / N. Manset ; P. Forshay. Vol. 485 Astronomical Society of the Pacific, 2014. pp. 425-428 (Astronomical Society of the Pacific. Conference Proceedings, Vol. 485).

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