Issue
Dagstuhl Reports, Volume 7, Issue 9
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Dagstuhl Reports, Volume 7
Journal: Dagstuhl Reports (DagRep)
Publication Details
- published at: 2018-04-10
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- DBLP: db/journals/dagstuhl-reports/dagstuhl-reports7
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Document
Complete Issue
Dagstuhl Reports, Volume 7, Issue 9, September 2017, Complete Issue
Abstract
Dagstuhl Reports, Volume 7, Issue 9, September 2017, Complete Issue
Cite as
Dagstuhl Reports, Volume 7, Issue 9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{DagRep.7.9,
title = {{Dagstuhl Reports, Volume 7, Issue 9, September 2017, Complete Issue}},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {9},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.9},
URN = {urn:nbn:de:0030-drops-86817},
doi = {10.4230/DagRep.7.9},
annote = {Keywords: Dagstuhl Reports, Volume 7, Issue 9, September 2017, Complete Issue}
}
Document
Front Matter
Dagstuhl Reports, Table of Contents, Volume 7, Issue 9, 2017
Abstract
Table of Contents, Frontmatter
Cite as
Dagstuhl Reports, Volume 7, Issue 9, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{DagRep.7.9.i,
title = {{Dagstuhl Reports, Table of Contents, Volume 7, Issue 9, 2017}},
pages = {i--ii},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {9},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.9.i},
URN = {urn:nbn:de:0030-drops-86801},
doi = {10.4230/DagRep.7.9.i},
annote = {Keywords: Dagstuhl Reports, Table of Contents, Volume 7, Issue 9, 2017}
}
Document
Finite and Algorithmic Model Theory (Dagstuhl Seminar 17361)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 17361 "Finite and Algorithmic Model Theory".
Cite as
Anuj Dawar, Erich Grädel, Phokion G. Kolaitis, and Thomas Schwentick. Finite and Algorithmic Model Theory (Dagstuhl Seminar 17361). In Dagstuhl Reports, Volume 7, Issue 9, pp. 1-25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{dawar_et_al:DagRep.7.9.1,
author = {Dawar, Anuj and Gr\"{a}del, Erich and Kolaitis, Phokion G. and Schwentick, Thomas},
title = {{Finite and Algorithmic Model Theory (Dagstuhl Seminar 17361)}},
pages = {1--25},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {9},
editor = {Dawar, Anuj and Gr\"{a}del, Erich and Kolaitis, Phokion G. and Schwentick, Thomas},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.9.1},
URN = {urn:nbn:de:0030-drops-85863},
doi = {10.4230/DagRep.7.9.1},
annote = {Keywords: algorithms, database theory, descriptive complexity, finite model theory, independence logic, knowledge representation, model checking}
}
Document
Deduction Beyond First-Order Logic (Dagstuhl Seminar 17371)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 17371 "Deduction Beyond First-Order Logic." Much research in the past two decades was dedicated to automating first-order logic with equality. However, applications often need reasoning beyond this logic. This includes genuinely higher-order reasoning, reasoning in theories that are not finitely axiomatisable in first-order logic (such as those including transitive closure
operators or standard arithmetic on integers or reals), or reasoning by mathematical induction. Other practical problems need a mixture of first-order proof search and some more advanced reasoning (for instance, about higher-order formulas), or simply higher-level reasoning steps. The aim of the seminar was to bring together first-order automated reasoning experts and researchers working on deduction methods and tools that go beyond first-order logic. The seminar was dedicated to the exchange of ideas to facilitate the transition from first-order to more expressive settings.
Cite as
Jasmin Christian Blanchette, Carsten Fuhs, Viorica Sofronie-Stokkermans, and Cesare Tinelli. Deduction Beyond First-Order Logic (Dagstuhl Seminar 17371). In Dagstuhl Reports, Volume 7, Issue 9, pp. 26-46, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{blanchette_et_al:DagRep.7.9.26,
author = {Blanchette, Jasmin Christian and Fuhs, Carsten and Sofronie-Stokkermans, Viorica and Tinelli, Cesare},
title = {{Deduction Beyond First-Order Logic (Dagstuhl Seminar 17371)}},
pages = {26--46},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {9},
editor = {Blanchette, Jasmin Christian and Fuhs, Carsten and Sofronie-Stokkermans, Viorica and Tinelli, Cesare},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.9.26},
URN = {urn:nbn:de:0030-drops-85872},
doi = {10.4230/DagRep.7.9.26},
annote = {Keywords: Automated Deduction, Program Verification, Certification}
}
Document
Cybersafety in Modern Online Social Networks (Dagstuhl Reports 17372)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 17372 "Cybersafety in Modern Online Social Networks." The main motivation behind the seminar stems from the increased relevance of threats and challenges in the context of cybersafety, especially in modern online social networks, where the range of malicious activities perpetrated by malevolent actors is regrettably wide. These include spreading malware and spam, controlling and operating fake/compromised accounts, artificially manipulating the reputation of accounts and pages, and spreading false information as well as terrorist propaganda.The reasons for the success of such attacks are manifold. The users of social networking services tend to extend their trust of the services and profiles of their acquaintances to unknown users and other third parties: despite the service providers' attempts at keeping their audiences identifiable and accountable, creating a fake profile, also in another person's name, is very simple. Even partially or fully taking over a profile is comparatively easy, and comes with the benefit of the trust this profile has accrued over time, as many credentials are easy to acquire. Further, even seemingly innocuous issues such as the design and presentation of user interfaces can result in implications for cybersafety. The failure to understand the interfaces and ramifications of certain online actions can lead to extensive over-sharing. Even the limited information of partial profiles may be sufficient for abuse by inference on specific features only. This is especially worrisome for new or younger users of a system that might unknowingly expose information or have unwanted interactions simply due to not fully understanding the platform they are using.
Unfortunately, research in cybersafety has looked at the various sub-problems in isolation, almost exclusively relying on algorithms aimed at detecting malicious accounts that act similarly, or analyzing specific lingual patterns. This ultimately yields a cat-and-mouse game, mostly played on economic grounds, whereby social network operators attempt to make it more and more costly for fraudsters to evade detection, which unfortunately tends to fail to measure and address the impact of safety threats from the point of view of regular individuals.
This prompts the need for a multi-faceted, multi-disciplinary, holistic approach to advancing the state of knowledge on cybersafety in online social networks, and the ways in which it can be researched and protected. Ultimately, we want to work towards development of a cutting-edge research agenda and technical roadmap that will allow the community to develop and embed tools to detect malice within the systems themselves, and to design effective ways to enhance their safety online.
This seminar was intended to bring together researchers from synergistic research communities, including experts working on information and system security on one hand, and those with expertise in human/economic/sociological factors of security on the other.
More specifically, in the field of cybersafety, there exist a number of interconnected, complex issues that cannot be addressed in isolation, but have to be tackled and countered together. Moreover, it is necessary for these challenges to be studied under a multi-disciplinary light. Consequently, we identified and focused on the most relevant issues in cybersafety, and explored both current and emerging solutions. Specifically, we discussed four problems that are the most pressing both in terms of negative impact and potential danger on individuals and society, and challenging open research problems requiring a multi-disciplinary approach:
Cyberbullying & Hate Speech, CyberFraud & Scams, Reputation Manipulation & Fake Activities, and Propaganda.
Overall, the seminar was organized to include a number of long talks from senior experts in the field, covering the four main topics above, followed by a series of short talks from the participants about work in progress and recent results, and finally working groups to foster collaborations, brainstorming, and setting of a research agenda forward.
Cite as
Jeremy Blackburn, Emiliano De Cristofaro, Michael Sirivianos, and Thorsten Strufe. Cybersafety in Modern Online Social Networks (Dagstuhl Reports 17372). In Dagstuhl Reports, Volume 7, Issue 9, pp. 47-61, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{blackburn_et_al:DagRep.7.9.47,
author = {Blackburn, Jeremy and De Cristofaro, Emiliano and Sirivianos, Michael and Strufe, Thorsten},
title = {{Cybersafety in Modern Online Social Networks (Dagstuhl Reports 17372)}},
pages = {47--61},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {9},
editor = {Blackburn, Jeremy and De Cristofaro, Emiliano and Sirivianos, Michael and Strufe, Thorsten},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.9.47},
URN = {urn:nbn:de:0030-drops-85886},
doi = {10.4230/DagRep.7.9.47},
annote = {Keywords: Cybersafety, Online Social Networks, Security and Privacy, Legal and Ethical Issues on the Web}
}
Document
Recent Trends in Knowledge Compilation (Dagstuhl Seminar 17381)
Abstract
Knowledge compilation (KC) is a research topic which aims to investigate the possibility of circumventing the computational intractability of hard tasks, by preprocessing part of the available information, common to a number of instances. Pioneered almost three decades ago, KC is nowadays a very active research field, transversal to several areas within computer science. Among others, KC intersects knowledge representation, constraint satisfaction, algorithms, complexity theory, machine learning, and databases.
The results obtained so far take various forms, from theory (compilability settings, definition of target languages for KC, complexity results, succinctness results, etc.) to more practical results (development and evaluation of compilers and other preprocessors, applications to diagnosis, planning, automatic configuration, etc.). Recently, KC has been positioned as providing a systematic method for solving problems beyond NP, and also found applications in machine learning.
The goal of this Dagstuhl Seminar was to advance both aspects of KC, and to pave the way for a fruitful cross-fertilization between the topics, from theory to practice. The program included a mixture of long and short presentations, with discussions. Several long talks with a tutorial flavor introduced the participants to the variety of aspects in knowledge compilation and the diversity of techniques used. System presentations as well as an open problem session were also included in the program.
Cite as
Adnan Darwiche, Pierre Marquis, Dan Suciu, and Stefan Szeider. Recent Trends in Knowledge Compilation (Dagstuhl Seminar 17381). In Dagstuhl Reports, Volume 7, Issue 9, pp. 62-85, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{darwiche_et_al:DagRep.7.9.62,
author = {Darwiche, Adnan and Marquis, Pierre and Suciu, Dan and Szeider, Stefan},
title = {{Recent Trends in Knowledge Compilation (Dagstuhl Seminar 17381)}},
pages = {62--85},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {9},
editor = {Darwiche, Adnan and Marquis, Pierre and Suciu, Dan and Szeider, Stefan},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.9.62},
URN = {urn:nbn:de:0030-drops-85896},
doi = {10.4230/DagRep.7.9.62},
annote = {Keywords: Knowledge compilation, Constraints, Preprocessing, Probabilistic databases, Model counting}
}
Document
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 17382)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 17382 "Approaches and Applications of Inductive Programming". After a short introduction to the state of the art to
inductive programming research, an overview of the introductory tutorials, the talks, program demonstrations, and the outcomes of discussion groups is given.
Cite as
Ute Schmid, Stephen H. Muggleton, and Rishabh Singh. Approaches and Applications of Inductive Programming (Dagstuhl Seminar 17382). In Dagstuhl Reports, Volume 7, Issue 9, pp. 86-108, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{schmid_et_al:DagRep.7.9.86,
author = {Schmid, Ute and Muggleton, Stephen H. and Singh, Rishabh},
title = {{Approaches and Applications of Inductive Programming (Dagstuhl Seminar 17382)}},
pages = {86--108},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {9},
editor = {Schmid, Ute and Muggleton, Stephen H. and Singh, Rishabh},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.9.86},
URN = {urn:nbn:de:0030-drops-85909},
doi = {10.4230/DagRep.7.9.86},
annote = {Keywords: inductive program synthesis, inductive logic programming, probabilistic programming, end-user programming, human-like computing}
}
Document
Deep Learning for Computer Vision (Dagstuhl Seminar 17391)
Abstract
The field of computer vision engages in the goal to enable and enhance a machine’s ability to infer knowledge and information from spatial and visual input data. Recent advances in data-driven learning approaches, accelerated by increasing parallel computing power and a ubiquitous availability of large amounts of data, pushed the boundaries of almost every vision related subdomain. The most prominent example of these machine learning approaches is a so called deep neural network (DNN), which works as a general function approximator and can be trained to learn a mapping between given input and target output data. Research on and with these DNN is generally referred to as Deep Learning. Despite its high dimensional and complex input space, research in the field of computer vision was and still is one of the main driving forces for new development in machine and deep learning, and vice versa.
This seminar aims to discuss recent works on theoretical and practical advances in the field of deep learning itself as well as state-of-the-art results achieved by applying learning based approaches to various vision problems. Our diverse spectrum of topics includes theoretical and mathematical insights focusing on a better understanding of the fundamental concepts behind deep learning and a multitude of specific research topics facilitating an exchange of knowledge between peers of the research community.
Cite as
Daniel Cremers, Laura Leal-Taixé, and René Vidal. Deep Learning for Computer Vision (Dagstuhl Seminar 17391). In Dagstuhl Reports, Volume 7, Issue 9, pp. 109-125, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{cremers_et_al:DagRep.7.9.109,
author = {Cremers, Daniel and Leal-Taix\'{e}, Laura and Vidal, Ren\'{e}},
title = {{Deep Learning for Computer Vision (Dagstuhl Seminar 17391)}},
pages = {109--125},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {9},
editor = {Cremers, Daniel and Leal-Taix\'{e}, Laura and Vidal, Ren\'{e}},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.9.109},
URN = {urn:nbn:de:0030-drops-85912},
doi = {10.4230/DagRep.7.9.109},
annote = {Keywords: computer vision, convolutional networks, deep learning, machine learning}
}
Document
Body-Centric Computing (Dagstuhl Reports 17392)
Abstract
The rise of technology that can support the active human body – in contrast to the previously prevalent paradigm of interacting with computers while sitting still – such as wearables, quantified self systems and mobile computing highlights an opportunity for a new era of "body-centric computing". However, most work in this area has taken quite an instrumental perspective, focusing on achieving extrinsic performance objectives. Phenomenology, however, highlights that it is also important to support the experiential perspective of living an active life, that is, technology should also help people focus on their lived experiences and personal growth to deepen their understanding and engagement with their own bodies.
We find that despite the work on embodiment, the use of technology to support the corporeal, pulsating and felt body has been notably absent. We believe the reason for this is due to limited knowledge about how to understand, analyse and correlate the vast amount of data from the various sensors worn by individuals and populations in real-time so that we can present it in a way that it supports people's felt experience. In order to drive such an agenda that supports both instrumental and experiential perspectives of the active human body, this seminar brings together leading experts, including those who are central to the development of products and ideas relating to wearables, mobile computing, quantified self, data analysis and visualization, exertion games and computer sports science. The goal is to address key questions around the use of sensor data to support both instrumental and experiential perspectives of the active human body and to jump-start collaborations between people from different backgrounds to pioneer new approaches for a body-centric computing future.
Cite as
Steve Benford, Kristina Höök, Joseph Marshall, Florian Mueller, and Dag Svanes. Body-Centric Computing (Dagstuhl Reports 17392). In Dagstuhl Reports, Volume 7, Issue 9, pp. 126-149, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{benford_et_al:DagRep.7.9.126,
author = {Benford, Steve and H\"{o}\"{o}k, Kristina and Marshall, Joseph and Mueller, Florian and Svanes, Dag},
title = {{Body-Centric Computing (Dagstuhl Reports 17392)}},
pages = {126--149},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {9},
editor = {Benford, Steve and H\"{o}\"{o}k, Kristina and Marshall, Joseph and Mueller, Florian and Svanes, Dag},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.9.126},
URN = {urn:nbn:de:0030-drops-85926},
doi = {10.4230/DagRep.7.9.126},
annote = {Keywords: embodiment, Human Computer Interaction, mobile computing, quantified self}
}