@misc{21203,
  author       = {{Schlesiger, Laura}},
  title        = {{{Determinants of Loyalty in Online Communities: A Systematic  Literature Review}}},
  year         = {{2021}},
}

@misc{23381,
  author       = {{Dierkes, Johannes}},
  title        = {{{Konkurrent oder Komplementär? Eine empirische Analyse über das  Nutzerverhalten in Online-Communities in Folge einer Smart Product  Innovation}}},
  year         = {{2021}},
}

@misc{21266,
  author       = {{Krüger, Noah}},
  title        = {{{Raising Money for a Good Cause – An Econometric Analysis of Key Factors to Successful Personal and Charitable Crowdfunding Campaigns}}},
  year         = {{2021}},
}

@misc{21196,
  author       = {{Schröder, Felix}},
  title        = {{{Benchmarking digitaler Gebrauchtgütermärkte - Eine Analyse zur Entwicklung von Best Practices am Beispiel von Miele Professional}}},
  year         = {{2021}},
}

@misc{22262,
  author       = {{Werner, Timur}},
  title        = {{{„For developers, by developers”? – Analyzing the Impact of Programming Languages’ Major Releases on Online Q&A Behavior}}},
  year         = {{2021}},
}

@misc{21714,
  author       = {{Wittmann, Daniel}},
  title        = {{{Interdependente Geschäftsmodelle: Eine systematische Analyse von Relationen in Geschäftsmodell-Modellierungssprachen}}},
  year         = {{2021}},
}

@article{29152,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>In this article we combine Debreu’s (Proc Natl Acad Sci 38(10):886–893, 1952) social system with Hurwicz’s (Econ Design 1(1):1–14, 1994; Am Econ Rev 98(3):577–585, 2008) ideas of embedding a “desired” game form into a “natural” game form that includes all feasible behavior, even if it is “illegal” according to the desired form. For the resulting socio-legal system we extend Debreu’s concepts of a social system and its social equilibria to a socio-legal system with its Debreu–Hurwicz equilibria. We build on a more general version of social equilibrium due to Shafer and Sonnenschein (J Math Econ 2(3):345–348, 1975) that also generalizes the dc-mechanism of Koray and Yildiz (J Econ Theory 176:479–502, 2018) which relates implementation via mechanisms with implementation via rights structures as introduced by Sertel (Designing rights: invisible hand theorems, covering and membership. Tech. rep. Mimeo, Bogazici University, 2001). In the second part we apply and illustrate these new concepts via an application in the narrow welfarist framework of two person cooperative bargaining. There we provide in a socio-legal system based on Nash’s demand game an implementation of the Nash bargaining solution in Debreu–Hurwicz equilibrium.</jats:p>}},
  author       = {{Haake, Claus-Jochen and Trockel, Walter}},
  issn         = {{1434-4742}},
  journal      = {{Review of Economic Design}},
  publisher    = {{Springer}},
  title        = {{{Socio-legal systems and implementation of the Nash solution in Debreu–Hurwicz equilibrium}}},
  doi          = {{10.1007/s10058-021-00278-z}},
  year         = {{2021}},
}

@inproceedings{28199,
  author       = {{Pauck, Felix and Wehrheim, Heike}},
  booktitle    = {{2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)}},
  title        = {{{Jicer: Simplifying Cooperative Android App Analysis Tasks}}},
  doi          = {{10.1109/scam52516.2021.00031}},
  year         = {{2021}},
}

@unpublished{26645,
  author       = {{Bobolz, Jan and Eidens, Fabian and Heitjohann, Raphael and Fell, Jeremy}},
  publisher    = {{IACR eprint}},
  title        = {{{Cryptimeleon: A Library for Fast Prototyping of Privacy-Preserving Cryptographic Schemes}}},
  year         = {{2021}},
}

@techreport{33854,
  abstract     = {{Macrodiversity is a key technique to increase the capacity of mobile networks. It can be realized using coordinated multipoint (CoMP), simultaneously connecting users to multiple overlapping cells. Selecting which users to serve by how many and which cells is NP-hard but needs to happen continuously in real time as users move and channel state changes. Existing approaches often require strict assumptions about or perfect knowledge of the underlying radio system, its resource allocation scheme, or user movements, none of which is readily available in practice.

Instead, we propose three novel self-learning and self-adapting approaches using model-free deep reinforcement learning (DRL): DeepCoMP, DD-CoMP, and D3-CoMP. DeepCoMP leverages central observations and control of all users to select cells almost optimally. DD-CoMP and D3-CoMP use multi-agent DRL, which allows distributed, robust, and highly scalable coordination. All three approaches learn from experience and self-adapt to varying scenarios, reaching 2x higher Quality of Experience than other approaches. They have very few built-in assumptions and do not need prior system knowledge, making them more robust to change and better applicable in practice than existing approaches.}},
  author       = {{Schneider, Stefan Balthasar and Karl, Holger and Khalili, Ramin and Hecker, Artur}},
  keywords     = {{mobility management, coordinated multipoint, CoMP, cell selection, resource management, reinforcement learning, multi agent, MARL, self-learning, self-adaptation, QoE}},
  title        = {{{DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning}}},
  year         = {{2021}},
}

@inproceedings{29137,
  author       = {{Hansmeier, Tim}},
  booktitle    = {{HEART '21: Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies}},
  location     = {{Online}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{{Self-aware Operation of Heterogeneous Compute Nodes using the Learning Classifier System XCS}}},
  doi          = {{10.1145/3468044.3468055}},
  year         = {{2021}},
}

@inbook{26888,
  author       = {{Götte, Thorsten and Kolb, Christina and Scheideler, Christian and Werthmann, Julian}},
  booktitle    = {{Algorithms for Sensor Systems (ALGOSENSORS '21)}},
  issn         = {{0302-9743}},
  location     = {{Lisbon, Portgual}},
  title        = {{{Beep-And-Sleep: Message and Energy Efficient Set Cover}}},
  doi          = {{10.1007/978-3-030-89240-1_7}},
  year         = {{2021}},
}

@phdthesis{28683,
  abstract     = {{In den letzten Jahren haben sich Software-Ökosysteme als neue, erfolgreiche Geschäftsform etabliert. Unternehmen agieren hierbei als Anbieter von Software-Plattformen, auf denen Drittanbieter Softwarelösungen für den Markt anbieten können.  Etablierte Beispiele sind hierbei sogenannte App-Stores, die z.B. von Google oder Apple angeboten werden.

Beim Aufbau von Software-Ökosystemen müssen vom Plattformanbieter viele architektonische Entwurfsentscheidungen getroffen werden. Bisher gibt es keine Architekturrichtlinien und -werkzeuge, die den Entwurf einer Ökosystemarchitektur unterstützen. Dadurch fehlt hier systematisches, wiederverwendbares Wissen. Plattformanbieter müssen auf ad-hoc Entscheidungen zurückgreifen. Dies kann dann zu Problemen im Betrieb der Software-Plattformen führen, zu erhöhten Ausfallrisiken und Mehrkosten.

Der Mangel an Architekturwissen manifestiert sich konkret in zwei Gruppen von Herausforderungen: Erstens fehlt eine Wissensbasis zu Architekturalternativen und zweitens fehlt es an methodischem Wissen zu Entwicklung und Betrieb von Software-Ökosystemen. Eine Architekturwissensbasis würde Orientierungshilfen zu den Bestandteilen von Software-Ökosystemen und deren Abhängigkeiten geben, während methodisches Wissen die Erstellung dieser Systeme erleichtern würde.

In der Dissertation werden diese Herausforderungen durch die Entwicklung des Frameworks SecoArc für die Modellierung von Software-Ökosystemen angegangen. Der Beitrag der Dissertation ist zweifach: 
1.	Das SecoArc-Framework umfasst eine Architekturwissensbasis, die wiederverwendbare Architekturentwurfsentscheidungen
von Software-Ökosystemen enthält. Die Wissensbasis wurde entwickelt, indem das Architekturwissen bestehender Ökosysteme sowie aus existierender Fachliteratur ermittelt wurde und in einer Produktlinie für Software-Ökosysteme konsolidiert wurde. Die Produktlinie umfasst architektonische Gemeinsamkeiten und Variabilitäten von Software-Ökosystemen. 
2.	Das SecoArc-Framework liefert methodisches Wissen, um die Ökosystemarchitektur in Modellen zu entwerfen und zu analysieren. Dieses Wissen wurde entwickelt, indem drei Architekturmuster identifiziert wurden. Jedes Muster erfasst unterschiedliche Beziehungen zwischen architektonischen Entwurfsentscheidungen zu den Qualitätsmerkmalen einer Ökosystemgesundheit und der Erreichung von Geschäftszielen. 

Die Architekturmuster und die Produktlinie wurden dazu genutzt, ein Modellierungsframework zu entwickeln und in Form eines Prototypen umzusetzen, welches einen Entwurfsprozess, eine Modellierungssprache und eine Architekturanalysetechnik umfasst. Es erleichtert das Modellieren, Analysieren und Vergleichen von Ökosystemarchitekturen.

Die Ergebnisse der Dissertation wurden im Rahmen von zwei Studien evaluiert. In der ersten Validierungsstudie wurden das Framework sowie der Prototyp verwendet, um zwei alternative Ökosystemarchitekturen zu entwerfen und zu analysieren. In der zweiten Studie wurde eine Analyse von existierenden Ökosystemen basierend auf den architektonischen Variabilitäten des Frameworks durchgeführt.}},
  author       = {{Schwichtenberg, Bahar}},
  keywords     = {{Enterprise Architecture, Architectural Design Decisions, Open Platforms}},
  title        = {{{Modeling and Analyzing Software Ecosystems}}},
  doi          = {{10.17619/UNIPB/1-1270 }},
  year         = {{2021}},
}

@inproceedings{29566,
  author       = {{Bobolz, Jan and Eidens, Fabian and Krenn, Stephan and Ramacher, Sebastian and Samelin, Kai}},
  booktitle    = {{Cryptology and Network Security}},
  isbn         = {{9783030925475}},
  issn         = {{0302-9743}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Issuer-Hiding Attribute-Based Credentials}}},
  doi          = {{10.1007/978-3-030-92548-2_9}},
  year         = {{2021}},
}

@inproceedings{23410,
  author       = {{Poniatowski, Martin and Neumann, Jürgen and Kundisch, Dennis}},
  location     = {{Newport Beach, California, USA}},
  title        = {{{Nudging Their Thoughts –  Analyzing the Impact of Online Review Templates on Review Sentiment}}},
  year         = {{2021}},
}

@inproceedings{23709,
  author       = {{Chen, Wei-Fan and Al Khatib, Khalid and Stein, Benno and Wachsmuth, Henning}},
  booktitle    = {{Findings of the Association for Computational Linguistics: EMNLP 2021}},
  pages        = {{2683 -- 2693}},
  title        = {{{Controlled Neural Sentence-Level Reframing of News Articles}}},
  year         = {{2021}},
}

@inproceedings{22229,
  author       = {{Alshomary, Milad and Syed, Shahbaz and Potthast, Martin and Wachsmuth, Henning}},
  booktitle    = {{Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)}},
  location     = {{Online}},
  pages        = {{1816–1827}},
  publisher    = {{Association for Computational Linguistics}},
  title        = {{{Argument Undermining: Counter-Argument Generation by Attacking Weak Premises}}},
  doi          = {{10.18653/v1/2021.findings-acl.159}},
  year         = {{2021}},
}

@inproceedings{21198,
  author       = {{Hanselle, Jonas Manuel and Tornede, Alexander and Wever, Marcel Dominik and Hüllermeier, Eyke}},
  location     = {{Delhi, India}},
  title        = {{{Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data}}},
  year         = {{2021}},
}

@inproceedings{21813,
  author       = {{Hansmeier, Tim and Platzner, Marco}},
  booktitle    = {{GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion}},
  isbn         = {{978-1-4503-8351-6}},
  location     = {{Lille, France}},
  pages        = {{1639–1647}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{{An Experimental Comparison of Explore/Exploit Strategies for the Learning Classifier System XCS}}},
  doi          = {{10.1145/3449726.3463159}},
  year         = {{2021}},
}

@techreport{35889,
  abstract     = {{Network and service coordination is important to provide modern services consisting of multiple interconnected components, e.g., in 5G, network function virtualization (NFV), or cloud and edge computing. In this paper, I outline my dissertation research, which proposes six approaches to automate such network and service coordination. All approaches dynamically react to the current demand and optimize coordination for high service quality and low costs. The approaches range from centralized to distributed methods and from conventional heuristic algorithms and mixed-integer linear programs to machine learning approaches using supervised and reinforcement learning. I briefly discuss their main ideas and advantages over other state-of-the-art approaches and compare strengths and weaknesses.}},
  author       = {{Schneider, Stefan Balthasar}},
  keywords     = {{nfv, coordination, machine learning, reinforcement learning, phd, digest}},
  title        = {{{Conventional and Machine Learning Approaches for Network and Service Coordination}}},
  year         = {{2021}},
}