Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12386/27641
DC Field | Value | Language |
---|---|---|
dc.contributor.author | BRESCIA, Massimo | en_US |
dc.contributor.author | CAVUOTI, STEFANO | en_US |
dc.contributor.author | Amaro, Valeria | en_US |
dc.contributor.author | RICCIO, GIUSEPPE | en_US |
dc.contributor.author | ANGORA, GIUSEPPE | en_US |
dc.contributor.author | Vellucci, Civita | en_US |
dc.contributor.author | Longo, Giuseppe | en_US |
dc.date.accessioned | 2020-10-07T08:14:10Z | - |
dc.date.available | 2020-10-07T08:14:10Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 978-3-319-96552-9 | en_US |
dc.identifier.issn | 1865-0929 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12386/27641 | - |
dc.description.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. | en_US |
dc.language.iso | eng | en_US |
dc.title | Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case | en_US |
dc.type | Book part | - |
dc.identifier.doi | 10.1007/978-3-319-96553-6_5 | en_US |
dc.identifier.scopus | 2-s2.0-85050374714 | en_US |
dc.identifier.url | https://link.springer.com/chapter/10.1007/978-3-319-96553-6_5 | en_US |
dc.relation.medium | STAMPA | en_US |
dc.relation.volume | 822 | en_US |
dc.relation.firstpage | 61 | en_US |
dc.relation.lastpage | 72 | en_US |
dc.relation.numberofpages | 12 | en_US |
dc.type.referee | REF_3 | en_US |
dc.description.numberofauthors | 7 | en_US |
dc.description.international | no | en_US |
dc.contributor.country | ITA | en_US |
dc.relation.allauthors | Kalinichenko, Leonid; Manolopoulos, Yannis; Malkov, Oleg; Skvortsov, Nikolay; Stupnikov, Sergey; Sukhomlin, Vladimir | en_US |
dc.relation.alleditors | Kalinichenko, Leonid ; Kuznetsov, Sergei O.; Manolopoulos, Yannis | - |
dc.relation.ispartofbook | Data Analytics and Management in Data Intensive Domains XIX International Conference, DAMDID/RCDL 2017 | en_US |
dc.publisher.name | Heidelberg ; New York ; Berlin : Springer | en_US |
dc.type.invited | no | - |
dc.relation.conferencename | Data Analytics and Management In Data Intensive Domains 2017 | - |
dc.relation.conferenceplace | Moscow, Russia | - |
dc.relation.conferencedate | October 10-13, 2017 | - |
dc.relation.scientificsector | FIS/05 - ASTRONOMIA E ASTROFISICA | en_US |
dc.type.miur | 268 Contributo in volume (Capitolo o Saggio) | - |
dc.relation.series | COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE | en_US |
dc.identifier.adsbibcode | 2018arXiv180207683B | en_US |
dc.relation.ercsector | ERC sectors::Physical Sciences and Engineering::PE9 Universe sciences: astro-physics/chemistry/biology; solar systems; stellar, galactic and extragalactic astronomy, planetary systems, cosmology, space science, instrumentation | en_US |
dc.description.apc | no | en_US |
dc.description.oa | 1 – prodotto con file in versione Open Access (allegare il file al passo 5-Carica) | en_US |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.openairetype | Book part | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | O.A. Capodimonte | - |
crisitem.author.dept | O.A. Capodimonte | - |
crisitem.author.dept | O.A. Capodimonte | - |
crisitem.author.orcid | 0000-0001-9506-5680 | - |
crisitem.author.orcid | 0000-0002-3787-4196 | - |
crisitem.author.orcid | 0000-0001-7020-1172 | - |
crisitem.journal.journalissn | 1865-0929 | - |
crisitem.journal.ance | E211396 | - |
Appears in Collections: | 2.01 Capitoli o saggi in libro |
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File | Description | Size | Format | |
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1802.07683.pdf | postprint | 590.51 kB | Adobe PDF | View/Open |
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Items in DSpace are published in Open Access, unless otherwise indicated.