BibTeX Export for Experimental Design for Any p-Norm

Copy to Clipboard Download

@InProceedings{lau_et_al:LIPIcs.APPROX/RANDOM.2023.4,
  author =	{Lau, Lap Chi and Wang, Robert and Zhou, Hong},
  title =	{{Experimental Design for Any p-Norm}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023)},
  pages =	{4:1--4:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-296-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{275},
  editor =	{Megow, Nicole and Smith, Adam},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2023.4},
  URN =		{urn:nbn:de:0030-drops-188292},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2023.4},
  annote =	{Keywords: Approximation Algorithm, Optimal Experimental Design, Randomized Local Search}
}

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