Dagstuhl Reports, Volume 8, Issue 9



Thumbnail PDF

Publication Details


Access Numbers

Documents

No documents found matching your filter selection.
Document
Complete Issue
Dagstuhl Reports, Volume 8, Issue 9, September 2018, Complete Issue

Abstract
Dagstuhl Reports, Volume 8, Issue 9, September 2018, Complete Issue

Cite as

Dagstuhl Reports, Volume 8, Issue 9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@Article{DagRep.8.9,
  title =	{{Dagstuhl Reports, Volume 8, Issue 9, September 2018, Complete Issue}},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{9},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.9},
  URN =		{urn:nbn:de:0030-drops-105602},
  doi =		{10.4230/DagRep.8.9},
  annote =	{Keywords: Dagstuhl Reports, Volume 8, Issue 9, September 2018, Complete Issue}
}
Document
Front Matter
Dagstuhl Reports, Table of Contents, Volume 8, Issue 9, 2018

Abstract
Dagstuhl Reports, Table of Contents, Volume 8, Issue 9, 2018

Cite as

Dagstuhl Reports, Volume 8, Issue 9, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@Article{DagRep.8.9.i,
  title =	{{Dagstuhl Reports, Table of Contents, Volume 8, Issue 9, 2018}},
  pages =	{i--ii},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{9},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.9.i},
  URN =		{urn:nbn:de:0030-drops-105599},
  doi =		{10.4230/DagRep.8.9.i},
  annote =	{Keywords: Table of Contents, Frontmatter}
}
Document
Measuring the Complexity of Computational Content: From Combinatorial Problems to Analysis (Dagstuhl Seminar 18361)

Authors: Vasco Brattka, Damir D. Dzhafarov, Alberto Marcone, and Arno Pauly


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 18361 "Measuring the Complexity of Computational Content: From Combinatorial Problems to Analysis". It includes abstracts of talks presented during the seminar and open problems that were discussed, as well as a bibliography on Weihrauch complexity that was started during the previous meeting (Dagstuhl seminar 15392) and that saw some significant growth in the meantime. The session "Solved problems" is dedicated to the solutions to some of the open questions raised in the previous meeting (Dagstuhl seminar 15392).

Cite as

Vasco Brattka, Damir D. Dzhafarov, Alberto Marcone, and Arno Pauly. Measuring the Complexity of Computational Content: From Combinatorial Problems to Analysis (Dagstuhl Seminar 18361). In Dagstuhl Reports, Volume 8, Issue 9, pp. 1-28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@Article{brattka_et_al:DagRep.8.9.1,
  author =	{Brattka, Vasco and Dzhafarov, Damir D. and Marcone, Alberto and Pauly, Arno},
  title =	{{Measuring the Complexity of Computational Content: From Combinatorial Problems to Analysis (Dagstuhl Seminar 18361)}},
  pages =	{1--28},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{9},
  editor =	{Brattka, Vasco and Dzhafarov, Damir D. and Marcone, Alberto and Pauly, Arno},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.9.1},
  URN =		{urn:nbn:de:0030-drops-103270},
  doi =		{10.4230/DagRep.8.9.1},
  annote =	{Keywords: Computability and complexity in analysis, computations on real numbers, reducibilities, descriptive complexity, computational complexity, reverse and}
}
Document
Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web (Dagstuhl Seminar 18371)

Authors: Piero Andrea Bonatti, Stefan Decker, Axel Polleres, and Valentina Presutti


Abstract
The increasingly pervasive nature of the Web, expanding to devices and things in everyday life, along with new trends in Artificial Intelligence call for new paradigms and a new look on Knowledge Representation and Processing at scale for the Semantic Web. The emerging, but still to be concretely shaped concept of "Knowledge Graphs" provides an excellent unifying metaphor for this current status of Semantic Web research. More than two decades of Semantic Web research provides a solid basis and a promising technology and standards stack to interlink data, ontologies and knowledge on the Web. However, neither are applications for Knowledge Graphs as such limited to Linked Open Data, nor are instantiations of Knowledge Graphs in enterprises - while often inspired by - limited to the core Semantic Web stack. This report documents the program and the outcomes of Dagstuhl Seminar 18371 "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web", where a group of experts from academia and industry discussed fundamental questions around these topics for a week in early September 2018, including the following: what are knowledge graphs? Which applications do we see to emerge? Which open research questions still need be addressed and which technology gaps still need to be closed?

Cite as

Piero Andrea Bonatti, Stefan Decker, Axel Polleres, and Valentina Presutti. Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web (Dagstuhl Seminar 18371). In Dagstuhl Reports, Volume 8, Issue 9, pp. 29-111, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@Article{bonatti_et_al:DagRep.8.9.29,
  author =	{Bonatti, Piero Andrea and Decker, Stefan and Polleres, Axel and Presutti, Valentina},
  title =	{{Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web (Dagstuhl Seminar 18371)}},
  pages =	{29--111},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{9},
  editor =	{Bonatti, Piero Andrea and Decker, Stefan and Polleres, Axel and Presutti, Valentina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.9.29},
  URN =		{urn:nbn:de:0030-drops-103283},
  doi =		{10.4230/DagRep.8.9.29},
  annote =	{Keywords: knowledge graphs, knowledge representation, linked data, ontologies, semantic web}
}
Document
Quantum Programming Languages (Dagstuhl Seminar 18381)

Authors: Michele Mosca, Martin Roetteler, and Peter Selinger


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 18381 "Quantum Programming Languages", which brought together researchers from quantum computing and classical programming languages.

Cite as

Michele Mosca, Martin Roetteler, and Peter Selinger. Quantum Programming Languages (Dagstuhl Seminar 18381). In Dagstuhl Reports, Volume 8, Issue 9, pp. 112-132, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@Article{mosca_et_al:DagRep.8.9.112,
  author =	{Mosca, Michele and Roetteler, Martin and Selinger, Peter},
  title =	{{Quantum Programming Languages (Dagstuhl Seminar 18381)}},
  pages =	{112--132},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{9},
  editor =	{Mosca, Michele and Roetteler, Martin and Selinger, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.9.112},
  URN =		{urn:nbn:de:0030-drops-103291},
  doi =		{10.4230/DagRep.8.9.112},
  annote =	{Keywords: compilers, functional programming, quantum computing, reversible computing, verification}
}
Document
Algebraic Methods in Computational Complexity (Dagstuhl Seminar 18391)

Authors: Markus Bläser, Valentine Kabanets, Jacobo Torán, and Christopher Umans


Abstract
Computational Complexity is concerned with the resources that are required for algorithms to detect properties of combinatorial objects and structures. It has often proven true that the best way to argue about these combinatorial objects is by establishing a connection (perhaps approximate) to a more well-behaved algebraic setting. Indeed, many of the deepest and most powerful results in Computational Complexity rely on algebraic proof techniques. The Razborov-Smolensky polynomial-approximation method for proving constant-depth circuit lower bounds, the PCP characterization of NP, and the Agrawal-Kayal-Saxena polynomial-time primality test are some of the most prominent examples. In some of the most exciting recent progress in Computational Complexity the algebraic theme still plays a central role. There have been significant recent advances in algebraic circuit lower bounds, and the so-called chasm at depth 4 suggests that the restricted models now being considered are not so far from ones that would lead to a general result. There have been similar successes concerning the related problems of polynomial identity testing and circuit reconstruction in the algebraic model (and these are tied to central questions regarding the power of randomness in computation). Also the areas of derandomization and coding theory have experimented important advances. The seminar aimed to capitalize on recent progress and bring together researchers who are using a diverse array of algebraic methods in a variety of settings. Researchers in these areas are relying on ever more sophisticated and specialized mathematics and the goal of the seminar was to play an important role in educating a diverse community about the latest new techniques.

Cite as

Markus Bläser, Valentine Kabanets, Jacobo Torán, and Christopher Umans. Algebraic Methods in Computational Complexity (Dagstuhl Seminar 18391). In Dagstuhl Reports, Volume 8, Issue 9, pp. 133-153, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@Article{blaser_et_al:DagRep.8.9.133,
  author =	{Bl\"{a}ser, Markus and Kabanets, Valentine and Tor\'{a}n, Jacobo and Umans, Christopher},
  title =	{{Algebraic Methods in Computational Complexity (Dagstuhl Seminar 18391)}},
  pages =	{133--153},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{9},
  editor =	{Bl\"{a}ser, Markus and Kabanets, Valentine and Tor\'{a}n, Jacobo and Umans, Christopher},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.9.133},
  URN =		{urn:nbn:de:0030-drops-103438},
  doi =		{10.4230/DagRep.8.9.133},
  annote =	{Keywords: computational complexity, algebra, (de-) randomization, circuits, coding, lower bounds}
}
Document
Automating Data Science (Dagstuhl Seminar 18401)

Authors: Tijl De Bie, Luc De Raedt, Holger H. Hoos, and Padhraic Smyth


Abstract
Data science is concerned with the extraction of knowledge and insight, and ultimately societal or economic value, from data. It complements traditional statistics in that its object is data as it presents itself in the wild (often complex and heterogeneous, noisy, loosely structured, biased, etc.), rather than well-structured data sampled in carefully designed studies. It also has a strong computer science focus, and is related to popular areas such as big data, machine learning, data mining and knowledge discovery. Data science is becoming increasingly important with the abundance of big data, while the number of skilled data scientists is lagging. This has raised the question as to whether it is possible to automate data science in several contexts. First, from an artificial intelligence perspective, it is interesting to investigate whether (data) science (or portions of it) can be automated, as it is an activity currently requiring high levels of human expertise. Second, the field of machine learning has a long-standing interest in applying machine learning at the meta-level, in order to obtain better machine learning algorithms, yielding recent successes in automated parameter tuning, algorithm configuration and algorithm selection. Third, there is an interest in automating not only the model building process itself (cf. the Automated Statistician) but also in automating the preprocessing steps (data wrangling). This Dagstuhl seminar brought together researchers from all areas concerned with data science in order to study whether, to what extent, and how data science can be automated.

Cite as

Tijl De Bie, Luc De Raedt, Holger H. Hoos, and Padhraic Smyth. Automating Data Science (Dagstuhl Seminar 18401). In Dagstuhl Reports, Volume 8, Issue 9, pp. 154-181, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@Article{debie_et_al:DagRep.8.9.154,
  author =	{De Bie, Tijl and De Raedt, Luc and Hoos, Holger H. and Smyth, Padhraic},
  title =	{{Automating Data Science  (Dagstuhl Seminar 18401)}},
  pages =	{154--181},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{9},
  editor =	{De Bie, Tijl and De Raedt, Luc and Hoos, Holger H. and Smyth, Padhraic},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.9.154},
  URN =		{urn:nbn:de:0030-drops-103443},
  doi =		{10.4230/DagRep.8.9.154},
  annote =	{Keywords: artificial intelligence, automated machine learning, automated scientific discovery, data science, inductive programming}
}

Filters


Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail