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Documents authored by Santner, Thomas J.


Document
09181 Abstracts Collection – Sampling-based Optimization in the Presence of Uncertainty

Authors: Jürgen Branke, Barry L. Nelson, Warren Buckler Powell, and Thomas J. Santner

Published in: Dagstuhl Seminar Proceedings, Volume 9181, Sampling-based Optimization in the Presence of Uncertainty (2009)


Abstract
This Dagstuhl seminar brought together researchers from statistical ranking and selection; experimental design and response-surface modeling; stochastic programming; approximate dynamic programming; optimal learning; and the design and analysis of computer experiments with the goal of attaining a much better mutual understanding of the commonalities and differences of the various approaches to sampling-based optimization, and to take first steps toward an overarching theory, encompassing many of the topics above.

Cite as

Jürgen Branke, Barry L. Nelson, Warren Buckler Powell, and Thomas J. Santner. 09181 Abstracts Collection – Sampling-based Optimization in the Presence of Uncertainty. In Sampling-based Optimization in the Presence of Uncertainty. Dagstuhl Seminar Proceedings, Volume 9181, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


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@InProceedings{branke_et_al:DagSemProc.09181.1,
  author =	{Branke, J\"{u}rgen and Nelson, Barry L. and Powell, Warren Buckler and Santner, Thomas J.},
  title =	{{09181 Abstracts Collection – Sampling-based Optimization in the Presence of Uncertainty}},
  booktitle =	{Sampling-based Optimization in the Presence of Uncertainty},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9181},
  editor =	{J\"{u}rgen Branke and Barry L. Nelson and Warren Buckler Powell and Thomas J. Santner},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09181.1},
  URN =		{urn:nbn:de:0030-drops-21187},
  doi =		{10.4230/DagSemProc.09181.1},
  annote =	{Keywords: Optimal learning, optimization in the presence of uncertainty, simulation optimization, sequential experimental design, ranking and selection, random search, stochastic approximation, approximate dynamic programming}
}
Document
09181 Executive Summary – Sampling-based Optimization in the Presence of Uncertainty

Authors: Jürgen Branke, Barry L. Nelson, Warren Buckler Powell, and Thomas J. Santner

Published in: Dagstuhl Seminar Proceedings, Volume 9181, Sampling-based Optimization in the Presence of Uncertainty (2009)


Abstract
This Dagstuhl seminar brought together researchers from statistical ranking and selection; experimental design and response-surface modeling; stochastic programming; approximate dynamic programming; optimal learning; and the design and analysis of computer experiments with the goal of attaining a much better mutual understanding of the commonalities and differences of the various approaches to sampling-based optimization, and to take first steps toward an overarching theory, encompassing many of the topics above.

Cite as

Jürgen Branke, Barry L. Nelson, Warren Buckler Powell, and Thomas J. Santner. 09181 Executive Summary – Sampling-based Optimization in the Presence of Uncertainty. In Sampling-based Optimization in the Presence of Uncertainty. Dagstuhl Seminar Proceedings, Volume 9181, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


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@InProceedings{branke_et_al:DagSemProc.09181.2,
  author =	{Branke, J\"{u}rgen and Nelson, Barry L. and Powell, Warren Buckler and Santner, Thomas J.},
  title =	{{09181 Executive Summary – Sampling-based Optimization in the Presence of Uncertainty }},
  booktitle =	{Sampling-based Optimization in the Presence of Uncertainty},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9181},
  editor =	{J\"{u}rgen Branke and Barry L. Nelson and Warren Buckler Powell and Thomas J. Santner},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09181.2},
  URN =		{urn:nbn:de:0030-drops-21161},
  doi =		{10.4230/DagSemProc.09181.2},
  annote =	{Keywords: Optimal learning, optimization in the presence of uncertainty, simulation optimization, sequential experimental design, ranking and selection, random search, stochastic approximation, approximate dynamic programming}
}
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