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|Title:||Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case||Authors:||BRESCIA, Massimo
|Issue Date:||2018||Journal:||Communications in Computer and Information Science||Volume:||Data Analytics and Management in Data Intensive Domains XIX International Conference, DAMDID/RCDL 2017||Editors:||Kalinichenko, Leonid ; Kuznetsov, Sergei O.; Manolopoulos, Yannis||Series:||COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE||Number:||822||First Page:||61||Abstract:||Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the recent huge increase in the number of publications making use of this new approach. The usage of machine learning methods, however is still far from trivial and many problems still need to be solved. Using the evaluation of photometric redshifts as a case study, we outline the main problems and some ongoing efforts to solve them.||Conference Name:||Data Analytics and Management In Data Intensive Domains 2017||Conference Place:||Moscow, Russia||Conference Date:||October 10-13, 2017||URI:||http://hdl.handle.net/20.500.12386/27641||URL:||https://link.springer.com/chapter/10.1007/978-3-319-96553-6_5||ISSN:||1865-0929||ISBN:||978-3-319-96552-9||DOI:||10.1007/978-3-319-96553-6_5||Bibcode ADS:||2018arXiv180207683B||Fulltext:||open|
|Appears in Collections:||2.01 Capitoli o saggi in libro|
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