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Suche nach „[TC Grafenau]“ hat 211 Publikationen gefunden
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    TC Grafenau

    Zeitschriftenartikel

    Robert Hable

    Data-Based Decisions under Imprecise Probability and Least Favorable Models.

    International Journal of Approximate Reasoning, vol. 50, no. 4, pp. 642-654

    2009

    DOI: 10.1016/j.ijar.2008.03.009

    Abstract anzeigen

    Data-based decision theory under imprecise probability has to deal with optimization problems where direct solutions are often computationally intractable. Using the ΓΓ-minimax optimality criterion, the computational effort may significantly be reduced in the presence of a least favorable model. Buja [A. Buja, Simultaneously least favorable experiments. I. Upper standard functionals and sufficiency, Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 65 (1984) 367–384] derived a necessary and sufficient condition for the existence of a least favorable model in a special case. The present article proves that essentially the same result is valid in case of general coherent upper previsions. This is done mainly by topological arguments in combination with some of Le Cam’s decision theoretic concepts. It is shown how least favorable models could be used to deal with situations where the distribution of the data as well as the prior is allowed to be imprecise.

    TC Grafenau

    Zeitschriftenartikel

    Robert Hable

    Finite approximations of data-based decision problems under imprecise probabilities.

    International Journal of Approximate Reasoning, vol. 50, no. 7, pp. 1115-1128

    2009

    DOI: 10.1016/j.ijar.2009.05.003

    Abstract anzeigen

    In decision theory under imprecise probabilities, discretizations are a crucial topic because many applications involve infinite sets whereas most procedures in the theory of imprecise probabilities can only be calculated for finite sets so far. The present paper develops a method for discretizing sample spaces in data-based decision theory under imprecise probabilities. The proposed method turns an original decision problem into a discretized decision problem. It is shown that any solution of the discretized decision problem approximately solves the original problem. In doing so, it is pointed out that the commonly used method of natural extension can be most instable. A way to avoid this instability is presented which is sufficient for the purpose of the paper.

    DigitalAngewandte WirtschaftswissenschaftenTC Grafenau

    Beitrag (Sammelband oder Tagungsband)

    Michael Scholz

    From Consumer Preferences Towards Buying Decisions - Conjoint Analysis as Preference Measuring Method in Product Recommender Systems

    21st Bled eConference (Bled, Slovenia)

    2008

    DigitalAngewandte WirtschaftswissenschaftenTC Grafenau

    Buch (Monographie)

    F. Lehner, Michael Scholz, S. Wildner

    Wirtschaftsinformatik

    Eine Einführung

    2008

    ISBN: 978-3446415720

    TC Grafenau

    Beitrag (Sammelband oder Tagungsband)

    Robert Hable

    Data-Based Decisions under Imprecise Probability and Least Favorable Models

    And Supplements to the Article

    Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA'07) [July 16th - 19th 2007, Prague, Czech Republic]

    2007

    DigitalAngewandte WirtschaftswissenschaftenTC Grafenau

    Beitrag (Sammelband oder Tagungsband)

    S. Wildner, Michael Scholz

    Managing Knowledge Methodically

    Multikonferenz Wirtschaftsinformatik 2006

    2006

    ISBN: 978-3936771626

    TC Grafenau

    Beitrag (Sammelband oder Tagungsband)

    R. Raja, Nari Arunraj, Surya Prakasa Rao, K.

    Decision support system for multi objective optimization in cotton mixing

    Proceedings of the International Conference on Operational Research and Development (ICORD) [December 27th - 30th 2002, Anna University, Chennai, India]

    2002

    DigitalTC Grafenau

    Vortrag

    Dietmar Jakob

    Voice Assistants in the residental environment of elderly

    IRIXYS - Young Scientists’ Workshop, Online

    DigitalTC Grafenau

    Vortrag

    Sebastian Wilhelm

    Activity Monitoring reusing Home Infrastructure Data

    IRIXYS - Young Scientists’ Workshop, Online

    DigitalTC Grafenau

    Vortrag

    Dietmar Jakob, Sebastian Wilhelm

    Prozessablauf von automatisierten Datenerhebungen in privaten Haushalten – Erfahrungsbericht

    Data2Day 2020 - Konferenz für Big Data, Data Science und Machine Learning, Heidelberg (online)

    Abstract anzeigen

    Smarte Technologien erzeugen Datenströme, die unter anderem für personalisierte Mehrwertdienste genutzt werden können. Zur Entwicklung entsprechender Dienste und intelligenter Algorithmen ist es häufig notwendig, gelabelte Rohdaten zu sammeln.  Dabei sind neben den technischen Herausforderungen auch Datenschutzbestimmungen und ethische Fragestellungen zu berücksichtigen.  In unserem Vortrag präsentieren wir einen Erfahrungsbericht über die Erhebung von Stromverbrauchsdaten in 20 privaten Haushalten, beginnend bei der Auswahl der Testhaushalte, der Sicherstellung einer informierten Zustimmung, die Installation der technischen Komponenten bis zur Anonymisierung und Veröffentlichung der Daten.

    TC Grafenau

    Beitrag (Sammelband oder Tagungsband)

    E. Hüllermeier, Ali Fallah Tehrani

    On the VC-Dimension of the Choquet Integral

    Advances in Computational Intelligence, Part I: 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2012), vol. 297

    ISBN: 9783642317088