BibTeX Export for Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152)

Copy to Clipboard Download

@Article{darrell_et_al:DagRep.5.4.18,
  author =	{Darrell, Trevor and Kloft, Marius and Pontil, Massimiliano and R\"{a}tsch, Gunnar and Rodner, Erik},
  title =	{{Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152)}},
  pages =	{18--55},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2015},
  volume =	{5},
  number =	{4},
  editor =	{Darrell, Trevor and Kloft, Marius and Pontil, Massimiliano and R\"{a}tsch, Gunnar and Rodner, Erik},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.5.4.18},
  URN =		{urn:nbn:de:0030-drops-53497},
  doi =		{10.4230/DagRep.5.4.18},
  annote =	{Keywords: machine learning, computer vision, computational biology, transfer learning, domain adaptation}
}

The metadata provided by Dagstuhl Publishing on its webpages, as well as their export formats (such as XML or BibTeX) available at our website, is released under the CC0 1.0 Public Domain Dedication license. That is, you are free to copy, distribute, use, modify, transform, build upon, and produce derived works from our data, even for commercial purposes, all without asking permission. Of course, we are always happy if you provide a link to us as the source of the data.

Read the full CC0 1.0 legal code for the exact terms that apply: https://creativecommons.org/publicdomain/zero/1.0/legalcode

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