6 Search Results for "Herrmann, Peter"

Document
DOI: 10.4230/LIPIcs.SEA.2026.2
Different Scales of Randomness: Empirical Mixing Times of the Edge Switching and Curveball MCMC

Authors: Deepak Ajwani, Melvin Kallmayer, Alexander Leonhardt, Ulrich Meyer, Ryan O'Connor, and Manuel Penschuck

Published in: LIPIcs, Volume 371, 24th International Symposium on Experimental Algorithms (SEA 2026)

Abstract
The Fixed Degree Sequence Model (FDSM) asks for a uniform sample from the set of all simple graphs that match a prescribed degree sequence. It is typically implemented using Markov-Chain Monte-Carlo (MCMC) processes, such as Edge Switching or Curveball (and their variants). Yet despite decades of research, rigorous bounds on the mixing times of such processes remain impractical. Consequently, several experimental techniques have been used to derive "empirical lower bounds" on the mixing time. We address the following research questions: (1) Which commonly studied graph-theoretic properties serve as reliable empirical predictors for mixing of FDSM MCMC processes? (2) At what structural scales do these properties operate primarily (i. e., are they predominantly local or global in nature)? (3) How can these properties be characterised and quantified most effectively? To this end, we propose Claim, a novel systematic method to establish empirical lower bounds using learnt classifiers, and compare it to existing methods. Apart from interesting insights into the usage of machine learning for this problem, we also derive robust graph properties with respect to different randomisation algorithms. Although experimental in nature, these results may influence both theorist’s and algorithm engineer’s work on improved bounds and better algorithm respectively.
Cite as

Deepak Ajwani, Melvin Kallmayer, Alexander Leonhardt, Ulrich Meyer, Ryan O'Connor, and Manuel Penschuck. Different Scales of Randomness: Empirical Mixing Times of the Edge Switching and Curveball MCMC. In 24th International Symposium on Experimental Algorithms (SEA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 371, pp. 2:1-2:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{ajwani_et_al:LIPIcs.SEA.2026.2,
  author =	{Ajwani, Deepak and Kallmayer, Melvin and Leonhardt, Alexander and Meyer, Ulrich and O'Connor, Ryan and Penschuck, Manuel},
  title =	{{Different Scales of Randomness: Empirical Mixing Times of the Edge Switching and Curveball MCMC}},
  booktitle =	{24th International Symposium on Experimental Algorithms (SEA 2026)},
  pages =	{2:1--2:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-422-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{371},
  editor =	{Aum\"{u}ller, Martin and Finocchi, Irene},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2026.2},
  URN =		{urn:nbn:de:0030-drops-260062},
  doi =		{10.4230/LIPIcs.SEA.2026.2},
  annote =	{Keywords: Mixing Time, Graph Randomization, Machine Learning, Edge Switching}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2026.5
Bifunction and Interlevel Delaunay Trifiltrations

Authors: Ángel Javier Alonso, Michael Kerber, Tung Lam, Michael Lesnick, and Abhishek Rathod

Published in: LIPIcs, Volume 367, 42nd International Symposium on Computational Geometry (SoCG 2026)

Abstract
A key property of the Delaunay filtration is that it is topologically (i.e., weakly) equivalent to the offset (union-of-balls) filtration. Recently, this filtration has been extended to point clouds equipped with an ℝ-valued function, yielding a computable 2-parameter filtration that satisfies an analogous weak equivalence. Motivated in part by the study of time-varying data, we introduce a 3-parameter extension of the Delaunay filtration for point clouds equipped with an ℝ²-valued function, also satisfying an analogous weak equivalence. For a point cloud X ⊂ ℝ^d, our trifiltration has size O(|X|^{⌈(d+1)/2⌉+1}). We present an algorithm that computes this trifiltration in time O(|X|^{⌈d/2⌉+2}), together with an implementation. Our experiments demonstrate that the implementation can handle thousands of points in ℝ³, with memory growth that is nearly linear.
Cite as

Ángel Javier Alonso, Michael Kerber, Tung Lam, Michael Lesnick, and Abhishek Rathod. Bifunction and Interlevel Delaunay Trifiltrations. In 42nd International Symposium on Computational Geometry (SoCG 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 367, pp. 5:1-5:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{alonso_et_al:LIPIcs.SoCG.2026.5,
  author =	{Alonso, \'{A}ngel Javier and Kerber, Michael and Lam, Tung and Lesnick, Michael and Rathod, Abhishek},
  title =	{{Bifunction and Interlevel Delaunay Trifiltrations}},
  booktitle =	{42nd International Symposium on Computational Geometry (SoCG 2026)},
  pages =	{5:1--5:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-418-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{367},
  editor =	{Ahn, Hee-Kap and Hoffmann, Michael and Nayyeri, Amir},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2026.5},
  URN =		{urn:nbn:de:0030-drops-258118},
  doi =		{10.4230/LIPIcs.SoCG.2026.5},
  annote =	{Keywords: Delaunay triangulation, Multiparameter persistent homology, Interlevel, Bowyer-Watson}
}
Document
Invited Paper
DOI: 10.4230/OASIcs.RW.2024/2025.7
Modern Datalog: Concepts, Methods, Applications (Invited Paper)

Authors: Markus Krötzsch

Published in: OASIcs, Volume 138, Joint Proceedings of the 20th and 21st Reasoning Web Summer Schools (RW 2024 & RW 2025)

Abstract
Pure Datalog is arguably the most fundamental rule language, elegant and simple, but also often too limited to be useful in practice. This has motivated the introduction of many new expressive features, ranging from datatypes and related functions, over aggregates and semi-ring generalisations, to existential quantifiers and complex terms. In spite of their variety, all these approaches remain true to the nature of Datalog as a direct, pattern-based way of computing on structured data. We therefore find that a modern notion of Datalog is emerging, distinctly different from other approaches of logic programming and with its own set of related methods and applications. In this course, we introduce Datalog and its most common extensions, and explain when and how these features can be used together (which is often, but not always, safe to do). We further look at modern Datalog systems and some of their primary use cases. Hands-on work with Datalog and its extensions is done with the free Datalog engine https://knowsys.github.io/nemo-doc/. The course is accessible to all audiences and does not assume specific prior knowledge.
Cite as

Markus Krötzsch. Modern Datalog: Concepts, Methods, Applications (Invited Paper). In Joint Proceedings of the 20th and 21st Reasoning Web Summer Schools (RW 2024 & RW 2025). Open Access Series in Informatics (OASIcs), Volume 138, pp. 7:1-7:41, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{krotzsch:OASIcs.RW.2024/2025.7,
  author =	{Kr\"{o}tzsch, Markus},
  title =	{{Modern Datalog: Concepts, Methods, Applications}},
  booktitle =	{Joint Proceedings of the 20th and 21st Reasoning Web Summer Schools (RW 2024 \& RW 2025)},
  pages =	{7:1--7:41},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-405-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{138},
  editor =	{Artale, Alessandro and Bienvenu, Meghyn and Garc{\'\i}a, Yazm{\'\i}n Ib\'{a}\~{n}ez and Murlak, Filip},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.RW.2024/2025.7},
  URN =		{urn:nbn:de:0030-drops-250524},
  doi =		{10.4230/OASIcs.RW.2024/2025.7},
  annote =	{Keywords: Datalog, query language, knowlegde representation and reasoning, logic programming, Horn logic, SPARQL, datatypes and aggregation, lecture notes, tutorial}
}
Document
DOI: 10.4230/OASIcs.SpaceCHI.2025.18
Advancing Intelligent Personal Assistants for Human Spaceflight

Authors: Leonie Bensch, Oliver Bensch, and Tommy Nilsson

Published in: OASIcs, Volume 130, Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)

Abstract
The Artemis program and upcoming missions to Mars mark a new era of human space exploration that will require new tools to support astronaut autonomy in the absence of real-time communication with Earth. This paper investigates the role of voice-based intelligent personal assistants (IPAs) in future crewed space missions. Through semi-structured interviews with astronauts (n=3) and spaceflight experts (n=12), we identify key user-centered design requirements for IPAs in this uniquely constrained and safety-critical environment. Our thematic analysis reveals core requirements for flexibility, reliability, offline capability, and multimodal interaction. Drawing on these findings, we outline design guidelines for next-generation IPAs and discuss how technologies such as retrieval-augmented generation (RAG), knowledge graphs, and augmented reality should be combined to support flexible, reliable, and multimodal IPAs for future human spaceflight missions.
Cite as

Leonie Bensch, Oliver Bensch, and Tommy Nilsson. Advancing Intelligent Personal Assistants for Human Spaceflight. In Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025). Open Access Series in Informatics (OASIcs), Volume 130, pp. 18:1-18:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{bensch_et_al:OASIcs.SpaceCHI.2025.18,
  author =	{Bensch, Leonie and Bensch, Oliver and Nilsson, Tommy},
  title =	{{Advancing Intelligent Personal Assistants for Human Spaceflight}},
  booktitle =	{Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)},
  pages =	{18:1--18:18},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-384-3},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{130},
  editor =	{Bensch, Leonie and Nilsson, Tommy and Nisser, Martin and Pataranutaporn, Pat and Schmidt, Albrecht and Sumini, Valentina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SpaceCHI.2025.18},
  URN =		{urn:nbn:de:0030-drops-240082},
  doi =		{10.4230/OASIcs.SpaceCHI.2025.18},
  annote =	{Keywords: Conversational Assistant, Intelligent Personal Assistant, Artificial Intelligence, Astronaut, Human Spaceflight, Generative Pre-Trained Transformer (GPT), Retrieval Augmented Generation (RAG), Knowledge Graphs, Augmented Reality, Voice Assistant, Long Duration Spaceflight}
}
Document
Vision
DOI: 10.4230/TGDK.1.1.6
Towards Ordinal Data Science

Authors: Gerd Stumme, Dominik Dürrschnabel, and Tom Hanika

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Order is one of the main instruments to measure the relationship between objects in (empirical) data. However, compared to methods that use numerical properties of objects, the amount of ordinal methods developed is rather small. One reason for this is the limited availability of computational resources in the last century that would have been required for ordinal computations. Another reason - particularly important for this line of research - is that order-based methods are often seen as too mathematically rigorous for applying them to real-world data. In this paper, we will therefore discuss different means for measuring and ‘calculating’ with ordinal structures - a specific class of directed graphs - and show how to infer knowledge from them. Our aim is to establish Ordinal Data Science as a fundamentally new research agenda. Besides cross-fertilization with other cornerstone machine learning and knowledge representation methods, a broad range of disciplines will benefit from this endeavor, including, psychology, sociology, economics, web science, knowledge engineering, scientometrics.
Cite as

Gerd Stumme, Dominik Dürrschnabel, and Tom Hanika. Towards Ordinal Data Science. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 6:1-6:39, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{stumme_et_al:TGDK.1.1.6,
  author =	{Stumme, Gerd and D\"{u}rrschnabel, Dominik and Hanika, Tom},
  title =	{{Towards Ordinal Data Science}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{6:1--6:39},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.6},
  URN =		{urn:nbn:de:0030-drops-194801},
  doi =		{10.4230/TGDK.1.1.6},
  annote =	{Keywords: Order relation, data science, relational theory of measurement, metric learning, general algebra, lattices, factorization, approximations and heuristics, factor analysis, visualization, browsing, explainability}
}
Document
DOI: 10.4230/DagSemProc.08102.3
3. 08102 Outcome Working Group – Situational Awareness

Authors: Richard A. Kemmerer, Roland Bueschkes, Ali Fessi, Hartmut Koenig, Peter Herrmann, Stephen Wolthusen, Marko Jahnke, Hervé Debar, Ralph Holz, Tanja Zseby, and Dirk Haage

Published in: Dagstuhl Seminar Proceedings, Volume 8102, Perspectives Workshop: Network Attack Detection and Defense (2008)

Abstract
Situation awareness (SA) has been defined as "the perception of elements in the environment within a volume of time and space, the comprehension of their meaning, and the projection of their status in the near future" (Endsley, 1988, 1995b, 2000).
Cite as

Richard A. Kemmerer, Roland Bueschkes, Ali Fessi, Hartmut Koenig, Peter Herrmann, Stephen Wolthusen, Marko Jahnke, Hervé Debar, Ralph Holz, Tanja Zseby, and Dirk Haage. 3. 08102 Outcome Working Group – Situational Awareness. In Perspectives Workshop: Network Attack Detection and Defense. Dagstuhl Seminar Proceedings, Volume 8102, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{kemmerer_et_al:DagSemProc.08102.3,
  author =	{Kemmerer, Richard A. and Bueschkes, Roland and Fessi, Ali and Koenig, Hartmut and Herrmann, Peter and Wolthusen, Stephen and Jahnke, Marko and Debar, Herv\'{e} and Holz, Ralph and Zseby, Tanja and Haage, Dirk},
  title =	{{3. 08102 Outcome Working Group – Situational Awareness}},
  booktitle =	{Perspectives Workshop: Network Attack Detection and Defense},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8102},
  editor =	{Georg Carle and Falko Dressler and Richard A. Kemmerer and Hartmut K\"{o}nig and Christopher Kruegel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08102.3},
  URN =		{urn:nbn:de:0030-drops-14942},
  doi =		{10.4230/DagSemProc.08102.3},
  annote =	{Keywords: Intrusion detection and prevention, attack response and countermeasures, reactive security, automated security, survivability and self-protection, ma network monitoring, flow analysis, denial of service detection and response, event correlation}
}
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