Singer, Marco

[["dc.bibliographiccitation.firstpage","699"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Medizinische Klinik - Intensivmedizin und Notfallmedizin"],["dc.bibliographiccitation.lastpage","707"],["dc.bibliographiccitation.volume","114"],["dc.contributor.author","Friesecke, S."],["dc.contributor.author","Träger, K."],["dc.contributor.author","Schittek, G. A."],["dc.contributor.author","Molnar, Z."],["dc.contributor.author","Bach, F."],["dc.contributor.author","Kogelmann, K."],["dc.contributor.author","Bogdanski, R."],["dc.contributor.author","Weyland, A."],["dc.contributor.author","Nierhaus, A."],["dc.contributor.author","Nestler, F."],["dc.contributor.author","Olboeter, D."],["dc.contributor.author","Tomescu, D."],["dc.contributor.author","Jacob, D."],["dc.contributor.author","Haake, H."],["dc.contributor.author","Grigoryev, E."],["dc.contributor.author","Nitsch, M."],["dc.contributor.author","Baumann, A."],["dc.contributor.author","Quintel, M."],["dc.contributor.author","Schott, M."],["dc.contributor.author","Kielstein, J. T."],["dc.contributor.author","Meier-Hellmann, A."],["dc.contributor.author","Born, F."],["dc.contributor.author","Schumacher, U."],["dc.contributor.author","Singer, M."],["dc.contributor.author","Kellum, J."],["dc.contributor.author","Brunkhorst, F. M."],["dc.date.accessioned","2020-12-10T14:07:57Z"],["dc.date.available","2020-12-10T14:07:57Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1007/s00063-017-0342-5"],["dc.identifier.eissn","2193-6226"],["dc.identifier.issn","2193-6218"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/70342"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Internationales Register zur Nutzung des Adsorbers CytoSorb® bei Intensivpatienten"],["dc.title.alternative","International registry on the use of the CytoSorb® adsorber in ICU patients. Study protocol and preliminary results"],["dc.title.subtitle","Studienprotokoll und erste Ergebnisse"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","351"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Biometrika"],["dc.bibliographiccitation.lastpage","362"],["dc.bibliographiccitation.volume","103"],["dc.contributor.author","Singer, Marco"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.contributor.author","Munk, Axel"],["dc.contributor.author","Groot, Bert L. de"],["dc.date.accessioned","2017-09-07T11:44:53Z"],["dc.date.available","2017-09-07T11:44:53Z"],["dc.date.issued","2016"],["dc.description.abstract","We consider the partial least squares algorithm for dependent data and study the consequences of ignoring the dependence both theoretically and numerically. Ignoring nonstationary dependence structures can lead to inconsistent estimation, but a simple modification yields consistent estimation. A protein dynamics example illustrates the superior predictive power of the proposed method."],["dc.identifier.doi","10.1093/biomet/asw010"],["dc.identifier.gro","3141674"],["dc.identifier.isi","000377429000008"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8007"],["dc.language.iso","en"],["dc.notes.intern","WoS Import 2017-03-10 / Funder: German Research Foundation"],["dc.notes.status","final"],["dc.notes.submitter","PUB_WoS_Import"],["dc.relation.eissn","1464-3510"],["dc.relation.issn","0006-3444"],["dc.title","Partial least squares for dependent data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","123"],["dc.bibliographiccitation.journal","Journal of Machine Learning Research"],["dc.bibliographiccitation.lastpage","41"],["dc.bibliographiccitation.volume","18"],["dc.contributor.author","Singer, Marco"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.contributor.author","Munk, Axel"],["dc.date.accessioned","2018-02-05T09:12:41Z"],["dc.date.available","2018-02-05T09:12:41Z"],["dc.date.issued","2017"],["dc.description.abstract","We consider the kernel partial least squares algorithm for non-parametric regression with stationary dependent data. Probabilistic convergence rates of the kernel partial least squares estimator to the true regression function are established under a source and an effective dimensionality condition. It is shown both theoretically and in simulations that long range dependence results in slower convergence rates. A protein dynamics example shows high predictive power of kernel partial least squares."],["dc.identifier.arxiv","1706.03559"],["dc.identifier.other","http://jmlr.org/papers/v18/17-306.html"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/11947"],["dc.language.iso","en"],["dc.notes.status","fcwi-famis"],["dc.title","Kernel Partial Least Squares for Stationary Data"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]