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64 Publications visible to you, out of a total of 64
Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs

Abstract

Not specified

Authors: Kai L. Polsterer, Fabian Gieseke, Christian Igel, Bernd Doser, Nikolaos Gianniotis

Date Published: 2016

Publication Type: InProceedings

On the application of machine learning approaches in astronomy: Exploring novel representations of high-dimensional and complex astronomical data

Abstract (Expand)

The goal of the presented work is the application of data-driven methods on complex and high- dimensional astronomical databases. The focus of the work is the exploration of novel data representations … in order to enable the use of statistical learning approaches in the analysis of data. With the help of diverse science cases, the advantages of the introduced approaches for classication, visualization and regression tasks are shown by applying the developed methodology to astronomical data. In the first part, an alternative approach for estimating redshifts of spectra by using the knowledge about the redshifts provided by the SDSS pipeline is presented. A novel data repre- sentation is employed which contains only information relevant for estimating the redshift and the detection of multiple redshift systems. Subsequently, a novel data representation for regu- larly sampled light curves based on recurrent networks is presented. This allows an explorative investigation of huge databases with unlabeled data. Finally, a new way of representing the static part of irregularly sampled light curves by a mixture of Gaussians is discussed. This represen- tation is more general than the extraction of features, as it allows the inclusion of photometric uncertainties and avoids the introduction of observational biases.

Author: Sven Dennis Kugler

Date Published: 9th Dec 2015

Publication Type: Doctoral Thesis

Analyzing Complex and Structured Data via Unsupervised Learning Techniques

Abstract

Not specified

Authors: K. L. Polsterer, F. Gieseke, N. Gianniotis, S. D. Kuegler

Date Published: 1st Aug 2015

Publication Type: Journal

Featureless classification of light curves

Abstract

Not specified

Authors: S. D. Kügler, N. Gianniotis, K. L. Polsterer

Date Published: 25th Jun 2015

Publication Type: Journal

Autoencoding Time Series for Visualisation

Abstract

Not specified

Authors: N. Gianniotis, S. D. Kügler, P. Tino, K. L. Polsterer, R. Misra

Date Published: 1st May 2015

Publication Type: InProceedings

Properties of optically selected BL Lacertae candidates from the SDSS

Abstract (Expand)

Context. Deep optical surveys open the avenue for finding large numbers of BL Lac objects that are hard to identify because they lack the unique properties classifying them as such. While radio or X-ray …ay surveys typically reveal dozens of sources, recent compilations based on optical criteria alone have increased the number of BL Lac candidates considerably. However, these compilations are subject to biases and may contain a substantial number of contaminating sources. Aims. In this paper we extend our analysis of 182 optically selected BL Lac object candidates from the SDSS with respect to an earlier study. The main goal is to determine the number of bona fide BL Lac objects in this sample. Methods. We examine their variability characteristics, determine their broad-band radio-UV spectral energy distributions (SEDs), and search for the presence of a host galaxy. In addition we present new optical spectra for 27 targets with improved signal-to-noise ratio with respect to the SDSS spectra. Results. At least 59% of our targets have shown variability between SDSS DR2 and our observations by more than 0.1–0.27 mag depending on the telescope used. A host galaxy was detected in 36% of our targets. The host galaxy type and luminosities are consistent with earlier studies of BL Lac host galaxies. Simple fits to broad-band SEDs for 104 targets of our sample derived synchrotron peak frequencies between 13.5 ≤ log 10(νpeak) ≤ 16 with a peak at log 10 ~ 14.5. Our new optical spectra do not reveal any new redshift for any of our objects. Thus the sample contains a large number of bona fide BL Lac objects and seems to contain a substantial fraction of intermediate-frequency peaked BL Lacs.

Authors: S. D. Kügler, K. Nilsson, J. Heidt, J. Esser, T. Schultz

Date Published: 1st Sep 2014

Publication Type: Journal

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

Abstract (Expand)

Regression tasks are common in astronomy, for instance, the estimation of the redshift or the metallicity of galaxies. Generating regression models, however, is often hindered by the heterogeneity of … the available input catalogs, which leads to missing data and/or features of differing explanatory power. In this work, we show how simple but effective feature selection schemes from data mining can be used to significantly improve the performance of regression models for photometric redshift and metallicity estimation (even without any particular knowledge of the input parameters' physical properties). Our framework tests huge amounts of possible feature combinations. Since corresponding (single-core) implementations are computationally very demanding, we make use of the massive computational resources provided by nowadays graphics processing units to significantly reduce the overall runtime. This renders an exhaustive search possible, as we demonstrate in our experimental evaluation. We conclude the work by discussing further applications of our approach in the context of large-scale astronomical learning settings.

Authors: K. L. Polsterer, F. Gieseke, Christian Igel, Tomotsugu Goto

Date Published: 1st May 2014

Publication Type: InProceedings

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