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Dagstuhl Reports, Volume 13, Issue 2

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Dagstuhl Seminars 23061, 23062, 23071, 23072, 23081, 23082, 23091, 23092 (Perspectives Workshop)

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Document
Complete Issue
DOI: 10.4230/DagRep.13.2
Dagstuhl Reports, Volume 13, Issue 2, February 2023, Complete Issue
Abstract
Dagstuhl Reports, Volume 13, Issue 2, February 2023, Complete Issue
Cite as

Dagstuhl Reports, Volume 13, Issue 2, pp. 1-243, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{DagRep.13.2,
  title =	{{Dagstuhl Reports, Volume 13, Issue 2, February 2023, Complete Issue}},
  pages =	{1--243},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2},
  URN =		{urn:nbn:de:0030-drops-191767},
  doi =		{10.4230/DagRep.13.2},
  annote =	{Keywords: Dagstuhl Reports, Volume 13, Issue 2, February 2023, Complete Issue}
}
Document
Front Matter
DOI: 10.4230/DagRep.13.2.i
Dagstuhl Reports, Table of Contents, Volume 13, Issue 2, 2023
Abstract
Dagstuhl Reports, Table of Contents, Volume 13, Issue 2, 2023
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Dagstuhl Reports, Volume 13, Issue 2, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{DagRep.13.2.i,
  title =	{{Dagstuhl Reports, Table of Contents, Volume 13, Issue 2, 2023}},
  pages =	{i--ii},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.i},
  URN =		{urn:nbn:de:0030-drops-191770},
  doi =		{10.4230/DagRep.13.2.i},
  annote =	{Keywords: Table of Contents, Frontmatter}
}
Document
DOI: 10.4230/DagRep.13.2.1
Scheduling (Dagstuhl Seminar 23061)

Authors: Nicole Megow, Benjamin J. Moseley, David Shmoys, Ola Svensson, Sergei Vassilvitskii, and Jens Schlöter

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23061 "Scheduling". The seminar focused on the emerging models for beyond-worst case algorithm design, in particular, recent approaches that incorporate learning. This includes models for the integration of learning into algorithm design that have been proposed recently and that have already demonstrated advances in the state-of-art for various scheduling applications: (i) scheduling with error-prone learned predictions, (ii) data-driven algorithm design, and (iii) stochastic and Bayesian learning in scheduling.
Cite as

Nicole Megow, Benjamin J. Moseley, David Shmoys, Ola Svensson, Sergei Vassilvitskii, and Jens Schlöter. Scheduling (Dagstuhl Seminar 23061). In Dagstuhl Reports, Volume 13, Issue 2, pp. 1-19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{megow_et_al:DagRep.13.2.1,
  author =	{Megow, Nicole and Moseley, Benjamin J. and Shmoys, David and Svensson, Ola and Vassilvitskii, Sergei and Schl\"{o}ter, Jens},
  title =	{{Scheduling (Dagstuhl Seminar 23061)}},
  pages =	{1--19},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  editor =	{Megow, Nicole and Moseley, Benjamin J. and Shmoys, David and Svensson, Ola and Vassilvitskii, Sergei and Schl\"{o}ter, Jens},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.1},
  URN =		{urn:nbn:de:0030-drops-191789},
  doi =		{10.4230/DagRep.13.2.1},
  annote =	{Keywords: scheduling, mathematical optimization, approximation algorithms, learning methods, uncertainty}
}
Document
DOI: 10.4230/DagRep.13.2.20
Programming Language Processing (Dagstuhl Seminar 23062)

Authors: Michael Pradel, Baishakhi Ray, Charles Sutton, and Eran Yahav

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23062 "Programming Language Processing" (PLP). The seminar brought together researchers and practitioners from three communities-software engineering, programming languages, and natural language processing- providing a unique opportunity for cross-fertilization and inter-disciplinary progress. We discussed machine learning models of code, integrating learning-based and traditional program analysis, and learning from natural language information associated with software. The seminar lead to a better understanding of the commonalities and differences between natural and programming languages, and an understanding of the challenges and opportunities in industry adoption of PLP.
Cite as

Michael Pradel, Baishakhi Ray, Charles Sutton, and Eran Yahav. Programming Language Processing (Dagstuhl Seminar 23062). In Dagstuhl Reports, Volume 13, Issue 2, pp. 20-32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{pradel_et_al:DagRep.13.2.20,
  author =	{Pradel, Michael and Ray, Baishakhi and Sutton, Charles and Yahav, Eran},
  title =	{{Programming Language Processing (Dagstuhl Seminar 23062)}},
  pages =	{20--32},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  editor =	{Pradel, Michael and Ray, Baishakhi and Sutton, Charles and Yahav, Eran},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.20},
  URN =		{urn:nbn:de:0030-drops-191799},
  doi =		{10.4230/DagRep.13.2.20},
  annote =	{Keywords: ML4PL, ML4SE, Neural Software Analysis}
}
Document
DOI: 10.4230/DagRep.13.2.33
From Big Data Theory to Big Data Practice (Dagstuhl Seminar 23071)

Authors: Martin Farach-Colton, Fabian Daniel Kuhn, Ronitt Rubinfeld, and Przemysław Uznański

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23071 "From Big Data Theory to Big Data Practice". Some recent advances in the theory of algorithms for big data - sublinear/local algorithms, streaming algorithms and external memory algorithms - have translated into impressive improvements in practice, whereas others have remained stubbornly resistant to useful implementations. This seminar aimed to glean lessons for those aspect of these algorithms that have led to practical implementation to see if the lessons learned can both improve the implementations of other theoretical ideas and to help guide the next generation of theoretical advances.
Cite as

Martin Farach-Colton, Fabian Daniel Kuhn, Ronitt Rubinfeld, and Przemysław Uznański. From Big Data Theory to Big Data Practice (Dagstuhl Seminar 23071). In Dagstuhl Reports, Volume 13, Issue 2, pp. 33-46, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{farachcolton_et_al:DagRep.13.2.33,
  author =	{Farach-Colton, Martin and Kuhn, Fabian Daniel and Rubinfeld, Ronitt and Uzna\'{n}ski, Przemys{\l}aw},
  title =	{{From Big Data Theory to Big Data Practice (Dagstuhl Seminar 23071)}},
  pages =	{33--46},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  editor =	{Farach-Colton, Martin and Kuhn, Fabian Daniel and Rubinfeld, Ronitt and Uzna\'{n}ski, Przemys{\l}aw},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.33},
  URN =		{urn:nbn:de:0030-drops-191809},
  doi =		{10.4230/DagRep.13.2.33},
  annote =	{Keywords: external memory, local algorithms, sublinear algorithms}
}
Document
DOI: 10.4230/DagRep.13.2.47
Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072)

Authors: Vincent Fortuin, Yingzhen Li, Kevin Murphy, Stephan Mandt, and Laura Manduchi

Abstract
Deep generative models, such as variational autoencoders, generative adversarial networks, normalizing flows, and diffusion probabilistic models, have attracted a lot of recent interest. However, we believe that several challenges hinder their more widespread adoption: (C1) the difficulty of objectively evaluating the generated data; (C2) challenges in designing scalable architectures for fast likelihood evaluation or sampling; and (C3) challenges related to finding reproducible, interpretable, and semantically meaningful latent representations. In this Dagstuhl Seminar, we have discussed these open problems in the context of real-world applications of deep generative models, including (A1) generative modeling of scientific data, (A2) neural data compression, and (A3) out-of-distribution detection. By discussing challenges C1-C3 in concrete contexts A1-A3, we have worked towards identifying commonly occurring problems and ways towards overcoming them. We thus foresee many future research collaborations to arise from this seminar and for the discussed ideas to form the foundation for fruitful avenues of future research. We proceed in this report by summarizing the main results of the seminar and then giving an overview of the different contributed talks and working group discussions.
Cite as

Vincent Fortuin, Yingzhen Li, Kevin Murphy, Stephan Mandt, and Laura Manduchi. Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072). In Dagstuhl Reports, Volume 13, Issue 2, pp. 47-70, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{fortuin_et_al:DagRep.13.2.47,
  author =	{Fortuin, Vincent and Li, Yingzhen and Murphy, Kevin and Mandt, Stephan and Manduchi, Laura},
  title =	{{Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072)}},
  pages =	{47--70},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  editor =	{Fortuin, Vincent and Li, Yingzhen and Murphy, Kevin and Mandt, Stephan and Manduchi, Laura},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.47},
  URN =		{urn:nbn:de:0030-drops-191817},
  doi =		{10.4230/DagRep.13.2.47},
  annote =	{Keywords: deep generative models, representation learning, generative modeling, neural data compression, out-of-distribution detection}
}
Document
DOI: 10.4230/DagRep.13.2.71
Agents on the Web (Dagstuhl Seminar 23081)

Authors: Olivier Boissier, Andrei Ciortea, Andreas Harth, Alessandro Ricci, and Danai Vachtsevanou

Abstract
Recent standardization on the Web of Things and (Social) Linked Data unlocks new practical use cases and new opportunities for research on Web-based multi-agent systems. While existing research on multi-agent systems can contribute to engineering adaptive and flexible Web-based systems, increased deployment of systems following the recent standards can bring new insight into engineering large-scale and open multi-agent systems. These developments motivate the need for a broader perspective that can only be achieved through a concerted effort of the research communities on Web Architecture and Web of Things, Semantic Web and Linked Data, and Autonomous Agents and Multi-Agent Systems. Thus, the main objective of the Dagstuhl Seminar 23081 on Agents on the Web was to investigate these new research opportunities, to support the transfer of knowledge and results across the different communities, and to create a network of leading scholars and practitioners around these topics. This report documents the seminar’s program and outcomes. To continue the joint work after the seminar, the seminar participants created the W3C Autonomous Agents on the Web (WebAgents) Community Group.
Cite as

Olivier Boissier, Andrei Ciortea, Andreas Harth, Alessandro Ricci, and Danai Vachtsevanou. Agents on the Web (Dagstuhl Seminar 23081). In Dagstuhl Reports, Volume 13, Issue 2, pp. 71-162, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{boissier_et_al:DagRep.13.2.71,
  author =	{Boissier, Olivier and Ciortea, Andrei and Harth, Andreas and Ricci, Alessandro and Vachtsevanou, Danai},
  title =	{{Agents on the Web (Dagstuhl Seminar 23081)}},
  pages =	{71--162},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  editor =	{Boissier, Olivier and Ciortea, Andrei and Harth, Andreas and Ricci, Alessandro and Vachtsevanou, Danai},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.71},
  URN =		{urn:nbn:de:0030-drops-191820},
  doi =		{10.4230/DagRep.13.2.71},
  annote =	{Keywords: Web Architecture, Web of Things, Semantic Web, Linked Data, Multi-Agent Systems}
}
Document
DOI: 10.4230/DagRep.13.2.163
Resilient Software Configuration and Infrastructure Code Analysis (Dagstuhl Seminar 23082)

Authors: Jürgen Cito, Ruzica Piskac, Mark Santolucito, Andy Zaidman, and Daniel Sokolowski

Abstract
Errors originating from infrastructure and their configurations are one of the major causes of system failures and system degradation, resulting in security vulnerabilities, application outages, and incorrect program executions. Investigating the root causes of such issues and remedies for them requires insight from different research perspectives, including systems, programming languages, software engineering, and verification. To facilitate progress in this field, this Dagstuhl Seminar brought together experts from academia and industry, enabling synergies between different software systems subareas. The seminar was a forum for cross-disciplinary discussions, bridged communities, and forged new conversations on new approaches. Emerging themes that were revealed during the seminar included a focus on Infrastructure as Code, the similarities and differences between configuration engineering and software engineering, the portability (or lack thereof) of program analysis techniques to configuration analysis, the design space of expressibility of configuration languages, and future challenges of analysis for safety, security, and auditing. The seminar led to new short-term and long-term collaborations and connections, including organizing additional workshops and a joint vision paper.
Cite as

Jürgen Cito, Ruzica Piskac, Mark Santolucito, Andy Zaidman, and Daniel Sokolowski. Resilient Software Configuration and Infrastructure Code Analysis (Dagstuhl Seminar 23082). In Dagstuhl Reports, Volume 13, Issue 2, pp. 163-182, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{cito_et_al:DagRep.13.2.163,
  author =	{Cito, J\"{u}rgen and Piskac, Ruzica and Santolucito, Mark and Zaidman, Andy and Sokolowski, Daniel},
  title =	{{Resilient Software Configuration and Infrastructure Code Analysis (Dagstuhl Seminar 23082)}},
  pages =	{163--182},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  editor =	{Cito, J\"{u}rgen and Piskac, Ruzica and Santolucito, Mark and Zaidman, Andy and Sokolowski, Daniel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.163},
  URN =		{urn:nbn:de:0030-drops-191836},
  doi =		{10.4230/DagRep.13.2.163},
  annote =	{Keywords: Computing infrastructure, Configuration, Program analysis}
}
Document
DOI: 10.4230/DagRep.13.2.183
Algorithmic Foundations of Programmable Matter (Dagstuhl Seminar 23091)

Authors: Aaron Becker, Sándor Fekete, Irina Kostitsyna, Matthew J. Patitz, Damien Woods, and Ioannis Chatzigiannakis

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23091, "Algorithmic Foundations of Programmable Matter", a new and emerging field that combines theoretical work on algorithms with a wide spectrum of practical applications that reach all the way from small-scale embedded systems to cyber-physical structures at nano-scale. The aim of this seminar was to bring together researchers from computational geometry, distributed computing, DNA computing, and swarm robotics who have worked on programmable matter to inform one another about the newest developments in each area and to discuss future models, approaches, and directions for new research. Similar to the first two Dagstuhl Seminars on programmable matter (16271 and 18331), we did focus on some basic problems, but also considered new problems that were now within reach to be studied.
Cite as

Aaron Becker, Sándor Fekete, Irina Kostitsyna, Matthew J. Patitz, Damien Woods, and Ioannis Chatzigiannakis. Algorithmic Foundations of Programmable Matter (Dagstuhl Seminar 23091). In Dagstuhl Reports, Volume 13, Issue 2, pp. 183-198, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{becker_et_al:DagRep.13.2.183,
  author =	{Becker, Aaron and Fekete, S\'{a}ndor and Kostitsyna, Irina and Patitz, Matthew J. and Woods, Damien and Chatzigiannakis, Ioannis},
  title =	{{Algorithmic Foundations of Programmable Matter (Dagstuhl Seminar 23091)}},
  pages =	{183--198},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  editor =	{Becker, Aaron and Fekete, S\'{a}ndor and Kostitsyna, Irina and Patitz, Matthew J. and Woods, Damien and Chatzigiannakis, Ioannis},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.183},
  URN =		{urn:nbn:de:0030-drops-191848},
  doi =		{10.4230/DagRep.13.2.183},
  annote =	{Keywords: computational geometry, distributed algorithms, DNA computing, programmable matter, swarm robotics}
}
Document
DOI: 10.4230/DagRep.13.2.199
A Human-Computer Interaction Perspective to Drive Change towards Sustainable Future (Dagstuhl Perspectives Workshop 23092)

Authors: Susanne Boll, Kaisa Väänänen, Nicola Bidwell, Marc Hassenzahl, and Robin Neuhaus

Abstract
In our everyday lives, people are constrained by routines, social expectation, and the soft and hard technologies and infrastructures that shape this. The way they approach things, think about things, are expected to be, and are governed is rarely questioned in terms of the finite nature of resources nor impacts of this. The challenge is to change the way people think and behave, and to reshape these very tools and expectations. However, change is exhausting, challenging, confronting, and requires support. Technology can provide such a support, BUT it would be naïve to assume that this change will happen without friction, without dispute, and without constraints. But on the other hand, most of the conveniences that need to be changed are predicated on a false and falacious assumption that we can go as much, as fast, as high, and as pleasantly as we want without any regard for others. In this workshop, we explored how human computer interaction can facilitate, require, or even enforce the path we should take to use less, do slower, or act differently. In this Dagstuhl Perspectives Workshop we discussed the contribution that HCI can make in light of the SDGs and what role HCI must play in informing and changing the behavior of individuals and collectives.
Cite as

Susanne Boll, Kaisa Väänänen, Nicola Bidwell, Marc Hassenzahl, and Robin Neuhaus. A Human-Computer Interaction Perspective to Drive Change towards Sustainable Future (Dagstuhl Perspectives Workshop 23092). In Dagstuhl Reports, Volume 13, Issue 2, pp. 199-241, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{boll_et_al:DagRep.13.2.199,
  author =	{Boll, Susanne and V\"{a}\"{a}n\"{a}nen, Kaisa and Bidwell, Nicola and Hassenzahl, Marc and Neuhaus, Robin},
  title =	{{A Human-Computer Interaction Perspective to Drive Change towards Sustainable Future (Dagstuhl Perspectives Workshop 23092)}},
  pages =	{199--241},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{13},
  number =	{2},
  editor =	{Boll, Susanne and V\"{a}\"{a}n\"{a}nen, Kaisa and Bidwell, Nicola and Hassenzahl, Marc and Neuhaus, Robin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.2.199},
  URN =		{urn:nbn:de:0030-drops-191853},
  doi =		{10.4230/DagRep.13.2.199},
  annote =	{Keywords: Dagstuhl Perspectives Workshop}
}

Filters

  • Authors
  • B
  • Becker, Aaron
  • Bidwell, Nicola
  • Boissier, Olivier
  • Boll, Susanne
  • C
  • Chatzigiannakis, Ioannis
  • Ciortea, Andrei
  • Cito, Jürgen
  • F
  • Farach-Colton, Martin
  • Fekete, Sándor
  • Fortuin, Vincent
  • H
  • Harth, Andreas
  • Hassenzahl, Marc
  • K
  • Kostitsyna, Irina
  • Kuhn, Fabian Daniel
  • L
  • Li, Yingzhen
  • M
  • Mandt, Stephan
  • Manduchi, Laura
  • Megow, Nicole
  • Moseley, Benjamin J.
  • Murphy, Kevin
  • N
  • Neuhaus, Robin
  • P
  • Patitz, Matthew J.
  • Piskac, Ruzica
  • Pradel, Michael
  • R
  • Ray, Baishakhi
  • Ricci, Alessandro
  • Rubinfeld, Ronitt
  • S
  • Santolucito, Mark
  • Schlöter, Jens
  • Shmoys, David
  • Sokolowski, Daniel
  • Sutton, Charles
  • Svensson, Ola
  • U
  • Uznański, Przemysław
  • V
  • Väänänen, Kaisa
  • Vachtsevanou, Danai
  • Vassilvitskii, Sergei
  • W
  • Woods, Damien
  • Y
  • Yahav, Eran
  • Z
  • Zaidman, Andy

  • Subjects
  • Computer systems organization
  • Computer systems organization → Robotics
  • Computing methodologies
  • Computing methodologies → Artificial intelligence
  • Computing methodologies → Kernel methods
  • Computing methodologies → Learning in probabilistic graphical models
  • Computing methodologies → Machine learning
  • Computing methodologies → Multi-agent systems
  • Computing methodologies → Unsupervised learning
  • Human-centered computing
  • Human-centered computing → Ubiquitous computing
  • Information systems
  • Information systems → Data structures
  • Information systems → World Wide Web
  • Mathematics of computing
  • Mathematics of computing → Combinatorial optimization
  • Networks
  • Networks → Network performance analysis
  • Security and privacy
  • Security and privacy → Operating systems security
  • Software and its engineering
  • Software and its engineering
  • Software and its engineering → Compilers
  • Software and its engineering → Parallel programming languages
  • Software and its engineering → Software design engineering
  • Theory of computation
  • Theory of computation → Approximation algorithms analysis
  • Theory of computation → Computational geometry
  • Theory of computation → Data structures design and analysis
  • Theory of computation → Distributed algorithms
  • Theory of computation → Models of computation
  • Theory of computation → Streaming, sublinear and near linear time algorithms
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