@article{25182,
  author       = {{Zhang, Yong and Wan, Gang and Lewis, Nicholas H. C. and Mars, Julian and Bone, Sharon E. and Steinrück, Hans-Georg and Lukatskaya, Maria R. and Weadock, Nicholas J. and Bajdich, Michal and Borodin, Oleg and Tokmakoff, Andrei and Toney, Michael F. and Maginn, Edward J.}},
  issn         = {{2380-8195}},
  journal      = {{ACS Energy Letters}},
  pages        = {{3458--3463}},
  title        = {{{Water or Anion? Uncovering the Zn2+ Solvation Environment in Mixed Zn(TFSI)2 and LiTFSI Water-in-Salt Electrolytes}}},
  doi          = {{10.1021/acsenergylett.1c01624}},
  volume       = {{6}},
  year         = {{2021}},
}

@article{25183,
  author       = {{Geise, Natalie R. and Kasse, Robert M. and Nelson Weker, Johanna and Steinrück, Hans-Georg and Toney, Michael F.}},
  issn         = {{0897-4756}},
  journal      = {{Chemistry of Materials}},
  pages        = {{7537--7545}},
  title        = {{{Quantification of Efficiency in Lithium Metal Negative Electrodes via Operando X-ray Diffraction}}},
  doi          = {{10.1021/acs.chemmater.1c02585}},
  volume       = {{33}},
  year         = {{2021}},
}

@article{25184,
  author       = {{Cao, Chuntian and Pollard, Travis P. and Borodin, Oleg and Mars, Julian E. and Tsao, Yuchi and Lukatskaya, Maria R. and Kasse, Robert M. and Schroeder, Marshall A. and Xu, Kang and Toney, Michael F. and Steinrück, Hans-Georg}},
  issn         = {{0897-4756}},
  journal      = {{Chemistry of Materials}},
  pages        = {{7315--7336}},
  title        = {{{Toward Unraveling the Origin of Lithium Fluoride in the Solid Electrolyte Interphase}}},
  doi          = {{10.1021/acs.chemmater.1c01744}},
  volume       = {{33}},
  year         = {{2021}},
}

@inproceedings{25203,
  author       = {{Alexandra Morim da Silva, Ana and Röder, Michael and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{The Semantic Web - {ISWC} 2021 - 20th International Semantic Web Conference, {ISWC} 2021, Virtual Event, October 24-28, 2021, Proceedings}},
  editor       = {{Hotho, Andreas and Blomqvist, Eva and Dietze, Stefan and Fokoue, Achille and Ding, Ying and M. Barnaghi, Payam and Haller, Armin and Dragoni, Mauro and Alani, Harith}},
  pages        = {{270--286}},
  publisher    = {{Springer}},
  title        = {{{Using Compositional Embeddings for Fact Checking}}},
  doi          = {{10.1007/978-3-030-88361-4\_16}},
  volume       = {{12922}},
  year         = {{2021}},
}

@inproceedings{25206,
  author       = {{Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{The Semantic Web - 18th International Conference, {ESWC} 2021, Virtual Event, June 6-10, 2021, Proceedings}},
  editor       = {{Verborgh, Ruben and Hose, Katja and Paulheim, Heiko and Champin, Pierre{-}Antoine and Maleshkova, Maria and Corcho, Oscar and Ristoski, Petar and Alam, Mehwish}},
  pages        = {{409--424}},
  publisher    = {{Springer}},
  title        = {{{Convolutional Complex Knowledge Graph Embeddings}}},
  doi          = {{10.1007/978-3-030-77385-4\_24}},
  volume       = {{12731}},
  year         = {{2021}},
}

@inproceedings{25208,
  author       = {{Speck, Ren{\'{e}} and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{15th {IEEE} International Conference on Semantic Computing, {ICSC} 2021, Laguna Hills, CA, USA, January 27-29, 2021}},
  pages        = {{298--305}},
  publisher    = {{{IEEE}}},
  title        = {{{Twitter Network Mimicking for Data Storage Benchmarking}}},
  doi          = {{10.1109/ICSC50631.2021.00057}},
  year         = {{2021}},
}

@article{25209,
  author       = {{Demir, Caglar and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}},
  journal      = {{CoRR}},
  title        = {{{A shallow neural model for relation prediction}}},
  volume       = {{abs/2101.09090}},
  year         = {{2021}},
}

@article{25210,
  author       = {{Ali, Waqas and Saleem, Muhammad and Yao, Bin and Hogan, Aidan and Ngonga Ngomo, Axel-Cyrille}},
  journal      = {{CoRR}},
  title        = {{{A Survey of RDF Stores \& SPARQL Engines for Querying Knowledge Graphs}}},
  volume       = {{abs/2102.13027}},
  year         = {{2021}},
}

@article{25211,
  author       = {{Vollmers, Daniel and Jalota, Rricha and Moussallem, Diego and Topiwala, Hardik and Ngonga Ngomo, Axel-Cyrille and Usbeck, Ricardo}},
  journal      = {{CoRR}},
  title        = {{{Knowledge Graph Question Answering using Graph-Pattern Isomorphism}}},
  volume       = {{abs/2103.06752}},
  year         = {{2021}},
}

@article{25213,
  author       = {{Sharma, Arnab and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille and Wehrheim, Heike}},
  journal      = {{CoRR}},
  title        = {{{MLCheck- Property-Driven Testing of Machine Learning Models}}},
  volume       = {{abs/2105.00741}},
  year         = {{2021}},
}

@article{25214,
  author       = {{Wilke, Adrian and Ngonga Ngomo, Axel-Cyrille}},
  journal      = {{CoRR}},
  title        = {{{Open Data Portal Germany (OPAL) Projektergebnisse}}},
  volume       = {{abs/2105.03161}},
  year         = {{2021}},
}

@article{25215,
  author       = {{Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}},
  journal      = {{CoRR}},
  title        = {{{Out-of-Vocabulary Entities in Link Prediction}}},
  volume       = {{abs/2105.12524}},
  year         = {{2021}},
}

@article{25217,
  author       = {{Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}},
  journal      = {{CoRR}},
  title        = {{{DRILL- Deep Reinforcement Learning for Refinement Operators in ALC}}},
  volume       = {{abs/2106.15373}},
  year         = {{2021}},
}

@inproceedings{25242,
  author       = {{Laux, Florian and Görzen, Thomas}},
  booktitle    = {{Proceedings of the 42nd International Conference on Information Systems (ICIS)}},
  title        = {{{Trust Me, I’m Confident – Are Confident Members of the Crowd Better at Evaluating Business Model Ideas?}}},
  year         = {{2021}},
}

@article{25272,
  author       = {{Engelkemeier, Katja and Sun, Aijia and Voswinkel, Dietrich and Grydin, Olexandr and Schaper, Mirko and Bremser, Wolfgang}},
  issn         = {{2196-0216}},
  journal      = {{ChemElectroChem}},
  pages        = {{2155--2168}},
  title        = {{{Zinc Anodizing: Structural Diversity of Anodic Zinc Oxide Controlled by the Type of Electrolyte}}},
  doi          = {{10.1002/celc.202100216}},
  year         = {{2021}},
}

@inproceedings{25278,
  abstract     = {{Using Service Function Chaining (SFC) in wireless networks became popular in many domains like networking and multimedia. It relies on allocating network resources to incoming SFCs requests, via a Virtual Network Embedding (VNE) algorithm, so that it optimizes the performance of the SFC. When the load of incoming requests -- competing for the limited network resources -- increases, it becomes challenging to decide which requests should be admitted and which one should be rejected. In this work, we propose a deep Reinforcement learning (RL) solution that can learn the admission policy for different dependencies, such as the service lifetime and the priority of incoming requests. We compare the deep RL solution to a first-come-first-serve baseline that admits a request whenever there are available resources. We show that deep RL outperforms the baseline and provides higher acceptance rate with low rejections even when there are enough resources.}},
  author       = {{Afifi, Haitham and Sauer, Fabian Jakob and Karl, Holger}},
  booktitle    = {{2021 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (ANTS'21)}},
  keywords     = {{reinforcement learning, admission control, wireless sensor networks}},
  title        = {{{Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding}}},
  year         = {{2021}},
}

@inproceedings{25281,
  abstract     = {{Wireless Acoustic Sensor Networks (WASNs) have a wide range of audio signal processing applications. Due to the spatial diversity of the microphone and their relative position to the acoustic source, not all microphones are equally useful for subsequent audio signal processing tasks, nor do they all have the same wireless data transmission rates. Hence, a central task in WASNs is to balance a microphone’s estimated acoustic utility against its transmission delay, selecting a best-possible subset of microphones to record audio signals.

In this work, we use reinforcement learning to decide if a microphone should be used or switched off to maximize the acoustic quality at low transmission delays, while minimizing switching frequency. In experiments with moving sources in a simulated acoustic environment, our method outperforms naive baseline comparisons}},
  author       = {{Afifi, Haitham and Guenther, Michael and Brendel, Andreas and Karl, Holger and Kellermann, Walter}},
  booktitle    = {{14. ITG Conference on Speech Communication (ITG 2021)}},
  keywords     = {{microphone utility, microphone selection, wireless acoustic sensor network, network delay, reinforcement learning}},
  title        = {{{Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering Network and Acoustic Utilities}}},
  year         = {{2021}},
}

@inproceedings{25293,
  author       = {{Gunther, Michael and Afifi, Haitham and Brendel, Andreas and Karl, Holger and Kellermann, Walter}},
  booktitle    = {{ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}},
  title        = {{{Network-Aware Optimal Microphone Channel Selection in Wireless Acoustic Sensor Networks}}},
  doi          = {{10.1109/icassp39728.2021.9414528}},
  year         = {{2021}},
}

@inproceedings{25331,
  author       = {{Brinkmann, Marcus and Dresen, Christian and Merget, Robert and Poddebniak, Damian and Müller, Jens and Somorovsky, Juraj and Schwenk, Jörg and Schinzel, Sebastian}},
  booktitle    = {{30th {USENIX} Security Symposium ({USENIX} Security 21)}},
  isbn         = {{978-1-939133-24-3}},
  pages        = {{4293--4310}},
  publisher    = {{{USENIX} Association}},
  title        = {{{ALPACA: Application Layer Protocol Confusion - Analyzing and Mitigating Cracks in TLS Authentication}}},
  year         = {{2021}},
}

@inproceedings{25332,
  author       = {{Merget, Robert and Brinkmann, Marcus and Aviram, Nimrod and Somorovsky, Juraj and Mittmann, Johannes and Schwenk, Jörg}},
  booktitle    = {{30th {USENIX} Security Symposium ({USENIX} Security 21)}},
  isbn         = {{978-1-939133-24-3}},
  pages        = {{213--230}},
  publisher    = {{{USENIX} Association}},
  title        = {{{Raccoon Attack: Finding and Exploiting Most-Significant-Bit-Oracles in TLS-DH(E)}}},
  year         = {{2021}},
}