@phdthesis{47837, author = {{Hansmeier, Tim}}, title = {{{XCS for Self-awareness in Autonomous Computing Systems}}}, year = {{2023}}, } @inproceedings{32407, abstract = {{Estimating the ground state energy of a local Hamiltonian is a central problem in quantum chemistry. In order to further investigate its complexity and the potential of quantum algorithms for quantum chemistry, Gharibian and Le Gall (STOC 2022) recently introduced the guided local Hamiltonian problem (GLH), which is a variant of the local Hamiltonian problem where an approximation of a ground state is given as an additional input. Gharibian and Le Gall showed quantum advantage (more precisely, BQP-completeness) for GLH with $6$-local Hamiltonians when the guiding vector has overlap (inverse-polynomially) close to 1/2 with a ground state. In this paper, we optimally improve both the locality and the overlap parameters: we show that this quantum advantage (BQP-completeness) persists even with 2-local Hamiltonians, and even when the guiding vector has overlap (inverse-polynomially) close to 1 with a ground state. Moreover, we show that the quantum advantage also holds for 2-local physically motivated Hamiltonians on a 2D square lattice. This makes a further step towards establishing practical quantum advantage in quantum chemistry.}}, author = {{Gharibian, Sevag and Hayakawa, Ryu and Gall, François Le and Morimae, Tomoyuki}}, booktitle = {{Proceedings of the 50th EATCS International Colloquium on Automata, Languages and Programming (ICALP)}}, number = {{32}}, pages = {{1--19}}, title = {{{Improved Hardness Results for the Guided Local Hamiltonian Problem}}}, doi = {{10.4230/LIPIcs.ICALP.2023.32}}, volume = {{261}}, year = {{2023}}, } @article{47868, author = {{Tenberge, Claudia}}, journal = {{Grundschule Sachunterricht}}, pages = {{28--34}}, title = {{{Ungeliebte Tiere in der Stadt}}}, volume = {{98}}, year = {{2023}}, } @book{47885, editor = {{Vidita Urboniene , • Athanasios Christopoulos, Aušra Pažeraite, Christos Chytas, Claudia Tenberge, Djurdja Timotijevic, Dobrivoje Lale Eric, Egle Vaivadiene, Felix Winkelnkemper, Gabrielė Stupurienė, Gražina Šmitienė, Heidi Kaarto, Ingrida Mereckaite, Julija Grigorjevaite, Kadri Mettis, Katarina Stekic, Kristof Van de Keere, Marjana Brkic, Michael Lenke, Mikko-Jussi Laakso, Paulius Lukas Tamošiūnas, Sofia Karlsson, Sven Hüsing, Jurga Turčinavičienė, Violeta Šlekienė, Mart Laanpere, and Vidita Urboniene }}, publisher = {{online}}, title = {{{A PRACTICAL HANDBOOK ON EFFECTIVE DEVELOPMENT AND IMPLEMENTATION OF STEAM TEACHING AT SCHOOL}}}, year = {{2023}}, } @article{48013, author = {{Liu, Ping and Schumann, Nils and Abele, Fabian and Ren, Fazheng and Hanke, Marcel and Xin, Yang and Hartmann, Andreas and Schlierf, Michael and Keller, Adrian and Lin, Weilin and Zhang, Yixin}}, issn = {{2574-0970}}, journal = {{ACS Applied Nano Materials}}, keywords = {{General Materials Science}}, publisher = {{American Chemical Society (ACS)}}, title = {{{Thermophoretic Analysis of Biomolecules across the Nanoscales in Self-Assembled Polymeric Matrices}}}, doi = {{10.1021/acsanm.3c03623}}, year = {{2023}}, } @inbook{46561, author = {{Schuster, Britt-Marie}}, booktitle = {{Kommunikative Praktiken im Nationalsozialismus}}, editor = {{Markewitz, Friedrich and Scholl, Stefan and Schubert, Katrin and Wilk, Nicole M.}}, isbn = {{9783847116127}}, keywords = {{Kommunikationsgeschichte}}, pages = {{143–171}}, publisher = {{V&R unipress}}, title = {{{»Das dankst du deinem Führer« – Adressierungspraktiken in der Widerstandskommunikation gegen den Nationalsozialismus}}}, doi = {{10.14220/9783737016124}}, volume = {{3}}, year = {{2023}}, } @book{48043, editor = {{Schuster, Britt-Marie and Markewitz, Friedrich and Wilk, Nicole M.}}, title = {{{Widerstandshandeln. Sprachliche Praktiken des Sich-Widersetzens zwischen 1933 und 1945}}}, volume = {{4}}, year = {{2023}}, } @article{48051, author = {{Humpert, Lynn and Wäschle, Moritz and Horstmeyer, Sarah and Anacker, Harald and Dumitrescu, Roman and Albers, Albert}}, issn = {{2212-8271}}, journal = {{Procedia CIRP}}, keywords = {{General Medicine}}, pages = {{693--698}}, publisher = {{Elsevier BV}}, title = {{{Stakeholder-oriented Elaboration of Artificial Intelligence use cases using the example of Special-Purpose engineering}}}, doi = {{10.1016/j.procir.2023.02.160}}, volume = {{119}}, year = {{2023}}, } @article{48059, author = {{Winkel, Fabian and Wallscheid, Oliver and Scholz, Peter and Böcker, Joachim}}, issn = {{2644-1284}}, journal = {{IEEE Open Journal of the Industrial Electronics Society}}, keywords = {{Electrical and Electronic Engineering, Industrial and Manufacturing Engineering, Control and Systems Engineering}}, pages = {{1--14}}, publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}, title = {{{Pseudo-Labeling Machine Learning Algorithm for Predictive Maintenance of Relays}}}, doi = {{10.1109/ojies.2023.3323870}}, year = {{2023}}, } @article{48058, author = {{Winkel, Fabian and Deuse-Kleinsteuber, Johannes and Böcker, Joachim}}, issn = {{0018-9529}}, journal = {{IEEE Transactions on Reliability}}, keywords = {{Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality}}, pages = {{1--14}}, publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}, title = {{{Run-to-Failure Relay Dataset for Predictive Maintenance Research With Machine Learning}}}, doi = {{10.1109/tr.2023.3255786}}, year = {{2023}}, } @inproceedings{47522, abstract = {{Artificial benchmark functions are commonly used in optimization research because of their ability to rapidly evaluate potential solutions, making them a preferred substitute for real-world problems. However, these benchmark functions have faced criticism for their limited resemblance to real-world problems. In response, recent research has focused on automatically generating new benchmark functions for areas where established test suites are inadequate. These approaches have limitations, such as the difficulty of generating new benchmark functions that exhibit exploratory landscape analysis (ELA) features beyond those of existing benchmarks.The objective of this work is to develop a method for generating benchmark functions for single-objective continuous optimization with user-specified structural properties. Specifically, we aim to demonstrate a proof of concept for a method that uses an ELA feature vector to specify these properties in advance. To achieve this, we begin by generating a random sample of decision space variables and objective values. We then adjust the objective values using CMA-ES until the corresponding features of our new problem match the predefined ELA features within a specified threshold. By iteratively transforming the landscape in this way, we ensure that the resulting function exhibits the desired properties. To create the final function, we use the resulting point cloud as training data for a simple neural network that produces a function exhibiting the target ELA features. We demonstrate the effectiveness of this approach by replicating the existing functions of the well-known BBOB suite and creating new functions with ELA feature values that are not present in BBOB.}}, author = {{Prager, Raphael Patrick and Dietrich, Konstantin and Schneider, Lennart and Schäpermeier, Lennart and Bischl, Bernd and Kerschke, Pascal and Trautmann, Heike and Mersmann, Olaf}}, booktitle = {{Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms}}, isbn = {{9798400702020}}, keywords = {{Benchmarking, Instance Generator, Black-Box Continuous Optimization, Exploratory Landscape Analysis, Neural Networks}}, pages = {{129–139}}, publisher = {{Association for Computing Machinery}}, title = {{{Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features}}}, doi = {{10.1145/3594805.3607136}}, year = {{2023}}, } @inproceedings{46297, abstract = {{Exploratory landscape analysis (ELA) in single-objective black-box optimization relies on a comprehensive and large set of numerical features characterizing problem instances. Those foster problem understanding and serve as basis for constructing automated algorithm selection models choosing the best suited algorithm for a problem at hand based on the aforementioned features computed prior to optimization. This work specifically points to the sensitivity of a substantial proportion of these features to absolute objective values, i.e., we observe a lack of shift and scale invariance. We show that this unfortunately induces bias within automated algorithm selection models, an overfitting to specific benchmark problem sets used for training and thereby hinders generalization capabilities to unseen problems. We tackle these issues by presenting an appropriate objective normalization to be used prior to ELA feature computation and empirically illustrate the respective effectiveness focusing on the BBOB benchmark set.}}, author = {{Prager, Raphael Patrick and Trautmann, Heike}}, booktitle = {{Applications of Evolutionary Computation}}, editor = {{Correia, João and Smith, Stephen and Qaddoura, Raneem}}, isbn = {{978-3-031-30229-9}}, pages = {{411–425}}, publisher = {{Springer Nature Switzerland}}, title = {{{Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis Features}}}, year = {{2023}}, } @inproceedings{46298, abstract = {{The design and choice of benchmark suites are ongoing topics of discussion in the multi-objective optimization community. Some suites provide a good understanding of their Pareto sets and fronts, such as the well-known DTLZ and ZDT problems. However, they lack diversity in their landscape properties and do not provide a mechanism for creating multiple distinct problem instances. Other suites, like bi-objective BBOB, possess diverse and challenging landscape properties, but their optima are not well understood and can only be approximated empirically without any guarantees.}}, author = {{Schäpermeier, Lennart and Kerschke, Pascal and Grimme, Christian and Trautmann, Heike}}, booktitle = {{Evolutionary Multi-Criterion Optimization}}, editor = {{Emmerich, Michael and Deutz, André and Wang, Hao and Kononova, Anna V. and Naujoks, Boris and Li, Ke and Miettinen, Kaisa and Yevseyeva, Iryna}}, isbn = {{978-3-031-27250-9}}, pages = {{291–304}}, publisher = {{Springer Nature Switzerland}}, title = {{{Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets}}}, year = {{2023}}, } @article{46299, abstract = {{The herein proposed Python package pflacco provides a set of numerical features to characterize single-objective continuous and constrained optimization problems. Thereby, pflacco addresses two major challenges in the area optimization. Firstly, it provides the means to develop an understanding of a given problem instance, which is crucial for designing, selecting, or configuring optimization algorithms in general. Secondly, these numerical features can be utilized in the research streams of automated algorithm selection and configuration. While the majority of these landscape features is already available in the R package flacco, our Python implementation offers these tools to an even wider audience and thereby promotes research interests and novel avenues in the area of optimization.}}, author = {{Prager, Raphael Patrick and Trautmann, Heike}}, issn = {{1063-6560}}, journal = {{Evolutionary Computation}}, pages = {{1–25}}, title = {{{Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python}}}, doi = {{10.1162/evco_a_00341}}, year = {{2023}}, } @inbook{48165, abstract = {{Paying taxes is a field of economic activity that has always been highly morally charged: the question of who pays how much or can avoid or evade the prescribed payments is always closely related to debate about a fair societal distribution of burdens. In the process of moralisation, therefore, faith communities such as the Catholic Church also repeatedly seized the floor to propagate certain norms. The article examines the contributions of theologians from Spain, the USA and West Germany in the 1940s and 1950s. It concludes that the norms of taxation they propagated differed greatly depending on the institutional and economic frameworks within which they operated. The analysis proves taxation to be a field of economic action and societal dispute where economics and morality are indissolubly interconnected.}}, author = {{Schönhärl, Korinna}}, booktitle = {{ Reassessing the Moral Economy Religion and Economic Ethics from Ancient Greece to the 20th Century}}, editor = {{Skambraks, Tanja and Lutz, Martin}}, isbn = {{9783031298349}}, keywords = {{Tax history, religious history: financial history, catholic church, history of economic thought}}, pages = {{237--258}}, publisher = {{Springer}}, title = {{{Tax Morale and the Church: How Catholic Clergies Adapted Norms of Paying Taxes to Secular Institutions (1940s–1950s)}}}, year = {{2023}}, } @inproceedings{47626, author = {{Rüther, Moritz Johannes and Klippstein, Sven Helge and Schmid, Hans-Joachim}}, booktitle = {{PARTEC International Congress on Particle Technology - Book of Abstracts}}, isbn = {{ 978-3-18-990139-9}}, issn = {{0083-5560}}, location = {{Nürnberg}}, pages = {{172 -- 176}}, publisher = {{VDI Verlag GmbH}}, title = {{{Correlation between SLS-Powder processability and particle properties }}}, year = {{2023}}, } @inbook{48218, author = {{Wallmeier, Nadine and Wich-Reif, Claudia}}, booktitle = {{Historische (Morpho-)Syntax des Deutschen}}, editor = {{Hetjens, Dominik and Lasch, Alexander and Roth, Kerstin}}, pages = {{35--53}}, title = {{{Vergleichskonstruktionen im Mittelniederdeutschen}}}, volume = {{14}}, year = {{2023}}, } @inbook{40916, author = {{Foerster, Anne}}, booktitle = {{Regentinnen und andere Stellvertreterfiguren Vom 10. bis zum 15. Jahrhundert}}, editor = {{Signori, Gabriela and Zey, Claudia}}, pages = {{11--30}}, publisher = {{De Gruyter}}, title = {{{Regierende Herrscherwitwen und die Angst vor Fremdherrschaft. Zum Verhältnis von Dynastie und Geschlecht}}}, doi = {{10.1515/9783111071879002}}, volume = {{111}}, year = {{2023}}, } @inproceedings{48289, author = {{Habernal, Ivan and Mireshghallah, Fatemehsadat and Thaine, Patricia and Ghanavati, Sepideh and Feyisetan, Oluwaseyi}}, booktitle = {{Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts}}, publisher = {{Association for Computational Linguistics}}, title = {{{Privacy-Preserving Natural Language Processing}}}, doi = {{10.18653/v1/2023.eacl-tutorials.6}}, year = {{2023}}, } @inproceedings{48288, author = {{Matzken, Cleo and Eger, Steffen and Habernal, Ivan}}, booktitle = {{Findings of the Association for Computational Linguistics: ACL 2023}}, publisher = {{Association for Computational Linguistics}}, title = {{{Trade-Offs Between Fairness and Privacy in Language Modeling}}}, doi = {{10.18653/v1/2023.findings-acl.434}}, year = {{2023}}, }