3 Search Results for "Zhang, Sam"

Document
Media Exposition
DOI: 10.4230/LIPIcs.SoCG.2022.67
Visualizing and Unfolding Nets of 4-Polytopes (Media Exposition)

Authors: Satyan L. Devadoss, Matthew S. Harvey, and Sam Zhang

Published in: LIPIcs, Volume 224, 38th International Symposium on Computational Geometry (SoCG 2022)

Abstract
Over a decade ago, it was shown that every edge unfolding of the Platonic solids was without self-overlap, yielding a valid net. Recent work has extended this property to their higher-dimensional analogs: the 4-cube, 4-simplex, and 4-orthoplex. We present an interactive visualization that allows the user to unfold these polytopes by drawing on their dual 1-skeleton graph.
Cite as

Satyan L. Devadoss, Matthew S. Harvey, and Sam Zhang. Visualizing and Unfolding Nets of 4-Polytopes (Media Exposition). In 38th International Symposium on Computational Geometry (SoCG 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 224, pp. 67:1-67:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{devadoss_et_al:LIPIcs.SoCG.2022.67,
  author =	{Devadoss, Satyan L. and Harvey, Matthew S. and Zhang, Sam},
  title =	{{Visualizing and Unfolding Nets of 4-Polytopes}},
  booktitle =	{38th International Symposium on Computational Geometry (SoCG 2022)},
  pages =	{67:1--67:4},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-227-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{224},
  editor =	{Goaoc, Xavier and Kerber, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2022.67},
  URN =		{urn:nbn:de:0030-drops-160759},
  doi =		{10.4230/LIPIcs.SoCG.2022.67},
  annote =	{Keywords: unfoldings, nets, polytopes}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.FSTTCS.2020.3
Convex Optimization and Dynamic Data Structure (Invited Talk)

Authors: Yin Tat Lee

Published in: LIPIcs, Volume 182, 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020)

Abstract
In the last three years, there are many breakthroughs in optimization such as nearly quadratic time algorithms for bipartite matching, linear programming algorithms that are as fast as Ax = b. All of these algorithms are based on a careful combination of optimization techniques and dynamic data structures. In this talk, we will explain the framework underlying all the recent breakthroughs. Joint work with Jan van den Brand, Michael B. Cohen, Sally Dong, Haotian Jiang, Tarun Kathuria, Danupon Nanongkai, Swati Padmanabhan, Richard Peng, Thatchaphol Saranurak, Aaron Sidford, Zhao Song, Di Wang, Sam Chiu-wai Wong, Guanghao Ye, Qiuyi Zhang.
Cite as

Yin Tat Lee. Convex Optimization and Dynamic Data Structure (Invited Talk). In 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 182, p. 3:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{lee:LIPIcs.FSTTCS.2020.3,
  author =	{Lee, Yin Tat},
  title =	{{Convex Optimization and Dynamic Data Structure}},
  booktitle =	{40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020)},
  pages =	{3:1--3:1},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-174-0},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{182},
  editor =	{Saxena, Nitin and Simon, Sunil},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2020.3},
  URN =		{urn:nbn:de:0030-drops-132440},
  doi =		{10.4230/LIPIcs.FSTTCS.2020.3},
  annote =	{Keywords: Convex Optimization, Dynamic Data Structure}
}
Document
CG Challenge
DOI: 10.4230/LIPIcs.SoCG.2020.83
Computing Low-Cost Convex Partitions for Planar Point Sets with Randomized Local Search and Constraint Programming (CG Challenge)

Authors: Da Wei Zheng, Jack Spalding-Jamieson, and Brandon Zhang

Published in: LIPIcs, Volume 164, 36th International Symposium on Computational Geometry (SoCG 2020)

Abstract
The Minimum Convex Partition problem (MCP) is a problem in which a point-set is used as the vertices for a planar subdivision, whose number of edges is to be minimized. In this planar subdivision, the outer face is the convex hull of the point-set, and the interior faces are convex. In this paper, we discuss and implement the approach to this problem using randomized local search, and different initialization techniques based on maximizing collinearity. We also solve small instances optimally using a SAT formulation. We explored this as part of the 2020 Computational Geometry Challenge, where we placed first as Team UBC.
Cite as

Da Wei Zheng, Jack Spalding-Jamieson, and Brandon Zhang. Computing Low-Cost Convex Partitions for Planar Point Sets with Randomized Local Search and Constraint Programming (CG Challenge). In 36th International Symposium on Computational Geometry (SoCG 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 164, pp. 83:1-83:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{zheng_et_al:LIPIcs.SoCG.2020.83,
  author =	{Zheng, Da Wei and Spalding-Jamieson, Jack and Zhang, Brandon},
  title =	{{Computing Low-Cost Convex Partitions for Planar Point Sets with Randomized Local Search and Constraint Programming}},
  booktitle =	{36th International Symposium on Computational Geometry (SoCG 2020)},
  pages =	{83:1--83:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-143-6},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{164},
  editor =	{Cabello, Sergio and Chen, Danny Z.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2020.83},
  URN =		{urn:nbn:de:0030-drops-122412},
  doi =		{10.4230/LIPIcs.SoCG.2020.83},
  annote =	{Keywords: convex partition, randomized local search, planar point sets}
}
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