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Documents authored by Huang, Hao

Found 3 Possible Name Variants:

Huang, Hao

Document
DOI: 10.4230/LIPIcs.APPROX-RANDOM.2015.78
Large Supports are Required for Well-Supported Nash Equilibria

Authors: Yogesh Anbalagan, Hao Huang, Shachar Lovett, Sergey Norin, Adrian Vetta, and Hehui Wu

Published in: LIPIcs, Volume 40, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2015)

Abstract
We prove that for any constant k and any epsilon < 1, there exist bimatrix win-lose games for which every epsilon-WSNE requires supports of cardinality greater than k. To do this, we provide a graph-theoretic characterization of win-lose games that possess epsilon-WSNE with constant cardinality supports. We then apply a result in additive number theory of Haight to construct win-lose games that do not satisfy the requirements of the characterization. These constructions disprove graph theoretic conjectures of Daskalakis, Mehta and Papadimitriou and Myers.
Cite as

Yogesh Anbalagan, Hao Huang, Shachar Lovett, Sergey Norin, Adrian Vetta, and Hehui Wu. Large Supports are Required for Well-Supported Nash Equilibria. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 40, pp. 78-84, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{anbalagan_et_al:LIPIcs.APPROX-RANDOM.2015.78,
  author =	{Anbalagan, Yogesh and Huang, Hao and Lovett, Shachar and Norin, Sergey and Vetta, Adrian and Wu, Hehui},
  title =	{{Large Supports are Required for Well-Supported Nash Equilibria}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2015)},
  pages =	{78--84},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-89-7},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{40},
  editor =	{Garg, Naveen and Jansen, Klaus and Rao, Anup and Rolim, Jos\'{e} D. P.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2015.78},
  URN =		{urn:nbn:de:0030-drops-52959},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2015.78},
  annote =	{Keywords: bimatrix games, well-supported Nash equilibria}
}

Huang, Haosheng

Document
Vision Paper
DOI: 10.4230/LIPIcs.COSIT.2019.19
The Future of Geographic Information Displays from GIScience, Cartographic, and Cognitive Science Perspectives (Vision Paper)

Authors: Tyler Thrash, Sara Lanini-Maggi, Sara I. Fabrikant, Sven Bertel, Annina Brügger, Sascha Credé, Cao Tri Do, Georg Gartner, Haosheng Huang, Stefan Münzer, and Kai-Florian Richter

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)

Abstract
With the development of modern geovisual analytics tools, several researchers have emphasized the importance of understanding users' cognitive, perceptual, and affective tendencies for supporting spatial decisions with geographic information displays (GIDs). However, most recent technological developments have focused on support for navigation in terms of efficiency and effectiveness while neglecting the importance of spatial learning. In the present paper, we will envision the future of GIDs that also support spatial learning in the context of large-scale navigation. Specifically, we will illustrate the manner in which GIDs have been (in the past) and might be (in the future) designed to be context-responsive, personalized, and supportive for active spatial learning from three different perspectives (i.e., GIScience, cartography, and cognitive science). We will also explain why this approach is essential for preventing the technological infantilizing of society (i.e., the reduction of our capacity to make decisions without technological assistance). Although these issues are common to nearly all emerging digital technologies, we argue that these issues become especially relevant in consideration of a person’s current and future locations.
Cite as

Tyler Thrash, Sara Lanini-Maggi, Sara I. Fabrikant, Sven Bertel, Annina Brügger, Sascha Credé, Cao Tri Do, Georg Gartner, Haosheng Huang, Stefan Münzer, and Kai-Florian Richter. The Future of Geographic Information Displays from GIScience, Cartographic, and Cognitive Science Perspectives (Vision Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 19:1-19:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{thrash_et_al:LIPIcs.COSIT.2019.19,
  author =	{Thrash, Tyler and Lanini-Maggi, Sara and Fabrikant, Sara I. and Bertel, Sven and Br\"{u}gger, Annina and Cred\'{e}, Sascha and Do, Cao Tri and Gartner, Georg and Huang, Haosheng and M\"{u}nzer, Stefan and Richter, Kai-Florian},
  title =	{{The Future of Geographic Information Displays from GIScience, Cartographic, and Cognitive Science Perspectives}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{19:1--19:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.19},
  URN =		{urn:nbn:de:0030-drops-111113},
  doi =		{10.4230/LIPIcs.COSIT.2019.19},
  annote =	{Keywords: visual displays, geographic information, cartography, cognitive science}
}

Huang, Yuanhao

Document
DOI: 10.4230/LIPIcs.WABI.2019.10
Jointly Embedding Multiple Single-Cell Omics Measurements

Authors: Jie Liu, Yuanhao Huang, Ritambhara Singh, Jean-Philippe Vert, and William Stafford Noble

Published in: LIPIcs, Volume 143, 19th International Workshop on Algorithms in Bioinformatics (WABI 2019)

Abstract
Many single-cell sequencing technologies are now available, but it is still difficult to apply multiple sequencing technologies to the same single cell. In this paper, we propose an unsupervised manifold alignment algorithm, MMD-MA, for integrating multiple measurements carried out on disjoint aliquots of a given population of cells. Effectively, MMD-MA performs an in silico co-assay by embedding cells measured in different ways into a learned latent space. In the MMD-MA algorithm, single-cell data points from multiple domains are aligned by optimizing an objective function with three components: (1) a maximum mean discrepancy (MMD) term to encourage the differently measured points to have similar distributions in the latent space, (2) a distortion term to preserve the structure of the data between the input space and the latent space, and (3) a penalty term to avoid collapse to a trivial solution. Notably, MMD-MA does not require any correspondence information across data modalities, either between the cells or between the features. Furthermore, MMD-MA’s weak distributional requirements for the domains to be aligned allow the algorithm to integrate heterogeneous types of single cell measures, such as gene expression, DNA accessibility, chromatin organization, methylation, and imaging data. We demonstrate the utility of MMD-MA in simulation experiments and using a real data set involving single-cell gene expression and methylation data.
Cite as

Jie Liu, Yuanhao Huang, Ritambhara Singh, Jean-Philippe Vert, and William Stafford Noble. Jointly Embedding Multiple Single-Cell Omics Measurements. In 19th International Workshop on Algorithms in Bioinformatics (WABI 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 143, pp. 10:1-10:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{liu_et_al:LIPIcs.WABI.2019.10,
  author =	{Liu, Jie and Huang, Yuanhao and Singh, Ritambhara and Vert, Jean-Philippe and Noble, William Stafford},
  title =	{{Jointly Embedding Multiple Single-Cell Omics Measurements}},
  booktitle =	{19th International Workshop on Algorithms in Bioinformatics (WABI 2019)},
  pages =	{10:1--10:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-123-8},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{143},
  editor =	{Huber, Katharina T. and Gusfield, Dan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2019.10},
  URN =		{urn:nbn:de:0030-drops-110401},
  doi =		{10.4230/LIPIcs.WABI.2019.10},
  annote =	{Keywords: Manifold alignment, single-cell sequencing}
}
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