Dagstuhl Reports, Volume 8, Issue 7



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Dagstuhl Seminars 18271, 18281, 18291

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Complete Issue
Dagstuhl Reports, Volume 8, Issue 7, July 2018, Complete Issue

Abstract
Dagstuhl Reports, Volume 8, Issue 7, July 2018, Complete Issue

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Dagstuhl Reports, Volume 8, Issue 7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{DagRep.8.7,
  title =	{{Dagstuhl Reports, Volume 8, Issue 7, July 2018, Complete Issue}},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{7},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.7},
  URN =		{urn:nbn:de:0030-drops-101788},
  doi =		{10.4230/DagRep.8.7},
  annote =	{Keywords: Dagstuhl Reports, Volume 8, Issue 7, July 2018, Complete Issue}
}
Document
Front Matter
Dagstuhl Reports, Table of Contents, Volume 8, Issue 7, 2018

Abstract
Dagstuhl Reports, Table of Contents, Volume 8, Issue 7, 2018

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Dagstuhl Reports, Volume 8, Issue 7, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{DagRep.8.7.i,
  title =	{{Dagstuhl Reports, Table of Contents, Volume 8, Issue 7, 2018}},
  pages =	{i--ii},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{7},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.7.i},
  URN =		{urn:nbn:de:0030-drops-101777},
  doi =		{10.4230/DagRep.8.7.i},
  annote =	{Keywords: Table of Contents, Frontmatter}
}
Document
In Situ Visualization for Computational Science (Dagstuhl Seminar 18271)

Authors: Janine C. Bennett, Hank Childs, Christoph Garth, and Bernd Hentschel


Abstract
In situ visualization, i.e., visualizing simulation data as it is generated, is an emerging processing paradigm in response to trends in the area of high-performance computing. This paradigm holds great promise in its ability to access increased spatio-temporal resolution and leverage extensive computational power. However, the paradigm is also widely viewed as limiting when it comes to exploration-oriented use cases and further will require visualization systems to become more and more complicated and constrained. Additionally, there are many open research topics with in situ visualization. The Dagstuhl seminar 18271 "In Situ Visualization for Computational Science" brought together researchers and practitioners from three communities (computational science, high-performance computing, and scientific visualization) to share interesting findings, to identify lines of open research, and to determine a medium-term research agenda that addresses the most pressing problems. This report summarizes the outcomes and findings of the seminar.

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Janine C. Bennett, Hank Childs, Christoph Garth, and Bernd Hentschel. In Situ Visualization for Computational Science (Dagstuhl Seminar 18271). In Dagstuhl Reports, Volume 8, Issue 7, pp. 1-43, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{bennett_et_al:DagRep.8.7.1,
  author =	{Bennett, Janine C. and Childs, Hank and Garth, Christoph and Hentschel, Bernd},
  title =	{{In Situ Visualization for Computational Science (Dagstuhl Seminar 18271)}},
  pages =	{1--43},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{7},
  editor =	{Bennett, Janine C. and Childs, Hank and Garth, Christoph and Hentschel, Bernd},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.7.1},
  URN =		{urn:nbn:de:0030-drops-101714},
  doi =		{10.4230/DagRep.8.7.1},
  annote =	{Keywords: In situ processing, scientific visualization, high-performance computing, computational science, Dagstuhl Seminar}
}
Document
Synergies between Adaptive Analysis of Algorithms, Parameterized Complexity, Compressed Data Structures and Compressed Indices (Dagstuhl Seminar 18281)

Authors: Jérémy Barbay, Johannes Fischer, Stefan Kratsch, and Srinivasa Rao Satti


Abstract
From the 8th of July 2018 to the 13th of July 2018, a Dagstuhl Seminar took place with the topic "Synergies between Adaptive Analysis of Algorithms, Parameterized Complexity, Compressed Data Structures and Compressed Indices". There, 40 participants from as many as 14 distinct countries and four distinct research areas, dealing with running time analysis and space usage analysis of algorithms and data structures, gathered to discuss results and techniques to "go beyond the worst-case" for classes of structurally restricted inputs, both for (fast) algorithms and (compressed) data structures. The seminar consisted of (1) a first session of personal introduction, each participant presenting his expertise and themes of interests in two slides; (2) a series of four technical talks; and (3) a larger series of presentations of open problems, with ample time left for the participants to gather and work on such open problems.

Cite as

Jérémy Barbay, Johannes Fischer, Stefan Kratsch, and Srinivasa Rao Satti. Synergies between Adaptive Analysis of Algorithms, Parameterized Complexity, Compressed Data Structures and Compressed Indices (Dagstuhl Seminar 18281). In Dagstuhl Reports, Volume 8, Issue 7, pp. 44-61, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{barbay_et_al:DagRep.8.7.44,
  author =	{Barbay, J\'{e}r\'{e}my and Fischer, Johannes and Kratsch, Stefan and Satti, Srinivasa Rao},
  title =	{{Synergies between Adaptive Analysis of Algorithms, Parameterized Complexity, Compressed Data Structures and Compressed Indices (Dagstuhl Seminar 18281)}},
  pages =	{44--61},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{7},
  editor =	{Barbay, J\'{e}r\'{e}my and Fischer, Johannes and Kratsch, Stefan and Satti, Srinivasa Rao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.7.44},
  URN =		{urn:nbn:de:0030-drops-101724},
  doi =		{10.4230/DagRep.8.7.44},
  annote =	{Keywords: adaptive (analysis of) algorithms, compressed data structures, compressed indices, parameterized complexity}
}
Document
Extreme Classification (Dagstuhl Seminar 18291)

Authors: Samy Bengio, Krzysztof Dembczynski, Thorsten Joachims, Marius Kloft, and Manik Varma


Abstract
Extreme classification is a rapidly growing research area within machine learning focusing on multi-class and multi-label problems involving an extremely large number of labels (even more than a million). Many applications of extreme classification have been found in diverse areas ranging from language modeling to document tagging in NLP, face recognition to learning universal feature representations in computer vision, gene function prediction in bioinformatics, etc. Extreme classification has also opened up a new paradigm for key industrial applications such as ranking and recommendation by reformulating them as multi-label learning tasks where each item to be ranked or recommended is treated as a separate label. Such reformulations have led to significant gains over traditional collaborative filtering and content-based recommendation techniques. Consequently, extreme classifiers have been deployed in many real-world applications in industry. Extreme classification has raised many new research challenges beyond the pale of traditional machine learning including developing log-time and log-space algorithms, deriving theoretical bounds that scale logarithmically with the number of labels, learning from biased training data, developing performance metrics, etc. The seminar aimed at bringing together experts in machine learning, NLP, computer vision, web search and recommendation from academia and industry to make progress on these problems. We believe that this seminar has encouraged the inter-disciplinary collaborations in the area of extreme classification, started discussion on identification of thrust areas and important research problems, motivated to improve the algorithms upon the state-of-the-art, as well to work on the theoretical foundations of extreme classification.

Cite as

Samy Bengio, Krzysztof Dembczynski, Thorsten Joachims, Marius Kloft, and Manik Varma. Extreme Classification (Dagstuhl Seminar 18291). In Dagstuhl Reports, Volume 8, Issue 7, pp. 62-80, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{bengio_et_al:DagRep.8.7.62,
  author =	{Bengio, Samy and Dembczynski, Krzysztof and Joachims, Thorsten and Kloft, Marius and Varma, Manik},
  title =	{{Extreme Classification (Dagstuhl Seminar 18291)}},
  pages =	{62--80},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{7},
  editor =	{Bengio, Samy and Dembczynski, Krzysztof and Joachims, Thorsten and Kloft, Marius and Varma, Manik},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.7.62},
  URN =		{urn:nbn:de:0030-drops-101739},
  doi =		{10.4230/DagRep.8.7.62},
  annote =	{Keywords: algorithms and complexity, artificial intelligence, computer vision, machine learning}
}

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