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Computationally and Statistically Efficient Inference for Complex Large-scale Data

dc.date.accessioned2019-10-24T15:15:47Z
dc.date.available2019-10-24T15:15:47Z
dc.date.issued2016
dc.identifier.urihttp://publications.mfo.de/handle/mfo/3520
dc.description.abstractThe aim of the highly successful workshop Computationally and statistically efficient inference for large-scale and heterogeneous data was to foster dissemination and collaboration between researchers in the area of highdimensional and large-scale data analysis. The field has grown tremendously over the last decade. Faced with ever larger data sets, many algorithms have emerged in computer science, machine learning and statistics that allow computationally efficient manipulation and model fitting on large datasets. Yet the mathematical and statistical properties of these algorithms are only just beginning to be understood. Advancing the field is important to avoid many misleading scientific discoveries based on pure data manipulation without the accompanying mathematical insights. The talks and discussions at the workshop covered the latest advances from optimization to statistical error control for large-scale data analysis.
dc.titleComputationally and Statistically Efficient Inference for Complex Large-scale Data
dc.rights.licenseDieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.de
dc.rights.licenseThis document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties.en
dc.identifier.doi10.14760/OWR-2016-16
local.series.idOWR-2016-16
local.subject.msc68
local.subject.msc62
local.sortindex960
local.date-range06 Mar - 12 Mar 2016
local.workshopcode1610
local.workshoptitleComputationally and Statistically Efficient Inference for Complex Large-scale Data
local.organizersGilles Blanchard, Potsdam; Nicolai Meinshausen, Zürich; Richard Samworth, Cambridge; Ming Yuan, Madison
local.report-nameWorkshop Report 2016,16
local.opc-photo-id1610
local.publishers-doi10.4171/OWR/2016/16
local.ems-referenceBlanchard Gilles, Meinshausen Nicolai, Samworth Richard, Yuan Ming: Computationally and Efficient Inference for Complex Large-scale Data. Oberwolfach Rep. 13 (2016), 741-796. doi: 10.4171/OWR/2016/16


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