5 Search Results for "Neumann, Thomas"

Document
DOI: 10.4230/LIPIcs.ITCS.2020.25
Distributional Property Testing in a Quantum World

Authors: András Gilyén and Tongyang Li

Published in: LIPIcs, Volume 151, 11th Innovations in Theoretical Computer Science Conference (ITCS 2020)

Abstract
A fundamental problem in statistics and learning theory is to test properties of distributions. We show that quantum computers can solve such problems with significant speed-ups. We also introduce a novel access model for quantum distributions, enabling the coherent preparation of quantum samples, and propose a general framework that can naturally handle both classical and quantum distributions in a unified manner. Our framework generalizes and improves previous quantum algorithms for testing closeness between unknown distributions, testing independence between two distributions, and estimating the Shannon / von Neumann entropy of distributions. For classical distributions our algorithms significantly improve the precision dependence of some earlier results. We also show that in our framework procedures for classical distributions can be directly lifted to the more general case of quantum distributions, and thus obtain the first speed-ups for testing properties of density operators that can be accessed coherently rather than only via sampling.
Cite as

András Gilyén and Tongyang Li. Distributional Property Testing in a Quantum World. In 11th Innovations in Theoretical Computer Science Conference (ITCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 151, pp. 25:1-25:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{gilyen_et_al:LIPIcs.ITCS.2020.25,
  author =	{Gily\'{e}n, Andr\'{a}s and Li, Tongyang},
  title =	{{Distributional Property Testing in a Quantum World}},
  booktitle =	{11th Innovations in Theoretical Computer Science Conference (ITCS 2020)},
  pages =	{25:1--25:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-134-4},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{151},
  editor =	{Vidick, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2020.25},
  URN =		{urn:nbn:de:0030-drops-117100},
  doi =		{10.4230/LIPIcs.ITCS.2020.25},
  annote =	{Keywords: distributional property testing, quantum algorithms, quantum query complexity}
}
Document
DOI: 10.4230/DagSemProc.08421.3
08421 Working Group: Classification, Representation and Modeling

Authors: Anish Das Sarma, Ander de Keijzer, Amol Deshpande, Peter J. Haas, Ihab F. Ilyas, Christoph Koch, Thomas Neumann, Dan Olteanu, Martin Theobald, and Vasilis Vassalos

Published in: Dagstuhl Seminar Proceedings, Volume 8421, Uncertainty Management in Information Systems (2009)

Abstract
This report briefly summarizes the discussions carried out in the working group on classification, representation and modeling of uncertain data. The discussion was divided into two subgroups: the first subgroup studied how different representation and modeling alternatives currently proposed can fit in a bigger picture of theory and technology interaction, while the second subgroup focused on contrasting current system implementations and the reasons behind such diverse class of available prototypes. We summarize the findings of these two groups and the future steps suggested by group members.
Cite as

Anish Das Sarma, Ander de Keijzer, Amol Deshpande, Peter J. Haas, Ihab F. Ilyas, Christoph Koch, Thomas Neumann, Dan Olteanu, Martin Theobald, and Vasilis Vassalos. 08421 Working Group: Classification, Representation and Modeling. In Uncertainty Management in Information Systems. Dagstuhl Seminar Proceedings, Volume 8421, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{dassarma_et_al:DagSemProc.08421.3,
  author =	{Das Sarma, Anish and de Keijzer, Ander and Deshpande, Amol and Haas, Peter J. and Ilyas, Ihab F. and Koch, Christoph and Neumann, Thomas and Olteanu, Dan and Theobald, Martin and Vassalos, Vasilis},
  title =	{{08421 Working Group: Classification, Representation and Modeling}},
  booktitle =	{Uncertainty Management in Information Systems},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{8421},
  editor =	{Christoph Koch and Birgitta K\"{o}nig-Ries and Volker Markl and Maurice van Keulen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.08421.3},
  URN =		{urn:nbn:de:0030-drops-19410},
  doi =		{10.4230/DagSemProc.08421.3},
  annote =	{Keywords: }
}
Document
DOI: 10.4230/DagSemProc.08091.11
Qualitative Abstraction and Inherent Uncertainty in Scene Recognition

Authors: Carsten Elfers, Otthein Herzog, Andrea Miene, and Thomas Wagner

Published in: Dagstuhl Seminar Proceedings, Volume 8091, Logic and Probability for Scene Interpretation (2008)

Abstract
The interpretation of scenes, e.g., in videos, is demanding at all levels. At the image processing level it is necessary to apply an "intelligent" segmentation and to determine the objects of interest. For the higher symbolic levels it is a challenging task to perform the transition between quantitative and qualitative data and to determine the relations between objects. Here we assume that the position of objects ("agents") in images and videos will already be determined as a minimal requirement for the further analysis. The interpretation of complex and dynamic scenes with embedded intentional agents is one of the most challenging tasks in current AI and imposes highly heterogeneous requirements. A key problem is the efficient and robust representation of uncertainty. We propose that uncertainty should be distinguished with respect to two different epistemological sources: (1) noisy sensor information and (2) ignorance. In this presentation we propose possible solutions to this class of problems. The use and evaluation of sensory information in the field of robotics shows impressive results especially in the fields of localization (e.g. MCL) and map building (e.g. SLAM) but also imposes serious problems on the successive higher levels of processing due to the probabilistic nature. In this presentation we propose that the use of (a) qualitative abstraction (classic approach) from quantitative to (at least partial) qualitative representations and (b) coherence-based perception validation based on Dempster-Shafer (DST) can help to reduce the problem significantly. The second important probability problem class that will be addressed is ignorance. In our presentation we will focus on reducing missing information by inference. We contrast/compare our experiences in an important field of scene interpretation namely plan and intention recognition. The first approach is based on a logical abductive approach and the second approach in contrast uses a probabilistic approach (Relational Hidden Markov Model (RHMM)).
Cite as

Carsten Elfers, Otthein Herzog, Andrea Miene, and Thomas Wagner. Qualitative Abstraction and Inherent Uncertainty in Scene Recognition. In Logic and Probability for Scene Interpretation. Dagstuhl Seminar Proceedings, Volume 8091, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{elfers_et_al:DagSemProc.08091.11,
  author =	{Elfers, Carsten and Herzog, Otthein and Miene, Andrea and Wagner, Thomas},
  title =	{{Qualitative Abstraction and Inherent Uncertainty in Scene Recognition}},
  booktitle =	{Logic and Probability for Scene Interpretation},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8091},
  editor =	{Anthony G. Cohn and David C. Hogg and Ralf M\"{o}ller and Bernd Neumann},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.08091.11},
  URN =		{urn:nbn:de:0030-drops-16141},
  doi =		{10.4230/DagSemProc.08091.11},
  annote =	{Keywords: Scene interpretation, intentional agents, uncertainty, qualitative abstraction, coherence-based perception, abduction, RHMM}
}
Document
DOI: 10.4230/DagSemProc.06061.8
Runtime Analysis of a Simple Ant Colony Optimization Algorithm

Authors: Frank Neumann and Carsten Witt

Published in: Dagstuhl Seminar Proceedings, Volume 6061, Theory of Evolutionary Algorithms (2006)

Abstract
Ant Colony Optimization (ACO) has become quite popular in recent years. In contrast to many successful applications, the theoretical foundation of this randomized search heuristic is rather weak. Building up such a theory is demanded to understand how these heuristics work as well as to come up with better algorithms for certain problems. Up to now, only convergence results have been achieved showing that optimal solutions can be obtained in a finite amount of time. We present the first runtime analysis of a simple ACO algorithm that transfers many rigorous results with respect to the expected runtime of a simple evolutionary algorithm to our algorithm. In addition, we examine the choice of the evaporation factor, which is a crucial parameter in such an algorithm, in greater detail and analyze its effect with respect to the runtime.
Cite as

Frank Neumann and Carsten Witt. Runtime Analysis of a Simple Ant Colony Optimization Algorithm. In Theory of Evolutionary Algorithms. Dagstuhl Seminar Proceedings, Volume 6061, pp. 1-17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{neumann_et_al:DagSemProc.06061.8,
  author =	{Neumann, Frank and Witt, Carsten},
  title =	{{Runtime Analysis of  a Simple Ant Colony Optimization Algorithm}},
  booktitle =	{Theory of Evolutionary Algorithms},
  pages =	{1--17},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6061},
  editor =	{Dirk V. Arnold and Thomas Jansen and Michael D. Vose and Jonathan E. Rowe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.06061.8},
  URN =		{urn:nbn:de:0030-drops-5928},
  doi =		{10.4230/DagSemProc.06061.8},
  annote =	{Keywords: Randomized Search Heuristics, Ant Colony Optimization, Runtime Analysis}
}
Document
DOI: 10.4230/DagSemProc.04401.10
On the Complexity of Parabolic Initial Value Problems with Variable Drift

Authors: Knut Petras and Klaus Ritter

Published in: Dagstuhl Seminar Proceedings, Volume 4401, Algorithms and Complexity for Continuous Problems (2005)

Abstract
We consider linear parabolic initial value problems of second order in several dimensions. The initial condition is supposed to be fixed and we investigate the comutational complexity if the coefficients of the parabolic equations may vary in certain function spaces. Using the parametrix method (or Neumann series), we prove that lower bounds for the error of numerical methods are related to lower bounds for integration problems. On the other hand, approximating the Neumann series with Smolyak's method, we show that the problem is not much harder than a certain approximation problem. For Hölder classes on compact sets, e.g., lower and upper bounds are close together, such that we have an almost optimal method.
Cite as

Knut Petras and Klaus Ritter. On the Complexity of Parabolic Initial Value Problems with Variable Drift. In Algorithms and Complexity for Continuous Problems. Dagstuhl Seminar Proceedings, Volume 4401, pp. 1-24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{petras_et_al:DagSemProc.04401.10,
  author =	{Petras, Knut and Ritter, Klaus},
  title =	{{On the Complexity of Parabolic Initial Value Problems with Variable Drift}},
  booktitle =	{Algorithms and Complexity for Continuous Problems},
  pages =	{1--24},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{4401},
  editor =	{Thomas M\"{u}ller-Gronbach and Erich Novak and Knut Petras and Joseph F. Traub},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.04401.10},
  URN =		{urn:nbn:de:0030-drops-1495},
  doi =		{10.4230/DagSemProc.04401.10},
  annote =	{Keywords: Partial differential equations , parabolic problems , Smolyak method , optimal methods}
}
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