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Foundations of Unsupervised Learning (Dagstuhl Seminar 16382)

Authors: Maria-Florina Balcan, Shai Ben-David, Ruth Urner, and Ulrike von Luxburg

Published in: Dagstuhl Reports, Volume 6, Issue 9 (2017)

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 16382 "Foundations of Unsupervised Learning". Unsupervised learning techniques are frequently used in practice of data analysis. However, there is currently little formal guidance as to how, when and to what effect to use which unsupervised learning method. The goal of the seminar was to initiate a broader and more systematic research on the foundations of unsupervised learning with the ultimate aim to provide more support to practitioners. The seminar brought together academic researchers from the fields of theoretical computer science and statistics as well as some researchers from industry.

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Maria-Florina Balcan, Shai Ben-David, Ruth Urner, and Ulrike von Luxburg. Foundations of Unsupervised Learning (Dagstuhl Seminar 16382). In Dagstuhl Reports, Volume 6, Issue 9, pp. 94-109, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@Article{balcan_et_al:DagRep.6.9.94,
  author =	{Balcan, Maria-Florina and Ben-David, Shai and Urner, Ruth and von Luxburg, Ulrike},
  title =	{{Foundations of Unsupervised Learning (Dagstuhl Seminar 16382)}},
  pages =	{94--109},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2017},
  volume =	{6},
  number =	{9},
  editor =	{Balcan, Maria-Florina and Ben-David, Shai and Urner, Ruth and von Luxburg, Ulrike},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.9.94},
  URN =		{urn:nbn:de:0030-drops-69542},
  doi =		{10.4230/DagRep.6.9.94},
  annote =	{Keywords: Machine learning, theory of computing, unsupervised learning, representation learning}
}

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Invited Talk

DOI: 10.4230/LIPIcs.MFCS.2016.1

How Far Are We From Having a Satisfactory Theory of Clustering? (Invited Talk)

Authors: Shai Ben-David

Published in: LIPIcs, Volume 58, 41st International Symposium on Mathematical Foundations of Computer Science (MFCS 2016)

Abstract

This is an overview of the invited talk delivered at the 41st International Symposium on Mathematical Foundations of Computer Science (MFCS-2016).

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Shai Ben-David. How Far Are We From Having a Satisfactory Theory of Clustering? (Invited Talk). In 41st International Symposium on Mathematical Foundations of Computer Science (MFCS 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 58, p. 1:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{bendavid:LIPIcs.MFCS.2016.1,
  author =	{Ben-David, Shai},
  title =	{{How Far Are We From Having a Satisfactory Theory of Clustering?}},
  booktitle =	{41st International Symposium on Mathematical Foundations of Computer Science (MFCS 2016)},
  pages =	{1:1--1:1},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-016-3},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{58},
  editor =	{Faliszewski, Piotr and Muscholl, Anca and Niedermeier, Rolf},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2016.1},
  URN =		{urn:nbn:de:0030-drops-65078},
  doi =		{10.4230/LIPIcs.MFCS.2016.1},
  annote =	{Keywords: clustering, theory, algorithm tuning, computational complexity}
}

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Documents authored by Ben-David, Shai

Foundations of Unsupervised Learning (Dagstuhl Seminar 16382)

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How Far Are We From Having a Satisfactory Theory of Clustering? (Invited Talk)

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