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5685 Publications
2019 | Conference Paper | LibreCat-ID: 13904 | 
Blömer, J., Bobolz, J., Diemert, D. P., & Eidens, F. (2019). Updatable Anonymous Credentials and Applications to Incentive Systems. Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security - CCS ’19. 26th ACM Conference on Computer and Communications Security, London. https://doi.org/10.1145/3319535.3354223
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2019 | Conference Paper | LibreCat-ID: 10108
Pauck, F., & Wehrheim, H. (2019). Together Strong: Cooperative Android App Analysis. Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 374–384. https://doi.org/10.1145/3338906.3338915
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2019 | Conference Paper | LibreCat-ID: 13874
Isenberg, T., Jakobs, M.-C., Pauck, F., & Wehrheim, H. (2019). When Are Software Verification Results Valid for Approximate Hardware? Tests and Proofs - 13th International Conference, {TAP} 2019, Held as Part of the Third World Congress on Formal Methods 2019, Porto, Portugal, October 9-11, 2019, Proceedings, 3–20. https://doi.org/10.1007/978-3-030-31157-5_1
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2019 | Journal Article | LibreCat-ID: 20243
Rohlfing, K., Leonardi, G., Nomikou, I., Rączaszek-Leonardi, J., & Hüllermeier, E. (2019). Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches. IEEE Transactions on Cognitive and Developmental Systems. https://doi.org/10.1109/TCDS.2019.2892991
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2019 | Conference Paper | LibreCat-ID: 13297 |
Gharibian, S., & Parekh, O. (2019). Almost Optimal Classical Approximation Algorithms for a Quantum Generalization of Max-Cut. Proceedings of the 22nd International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX), 145, 31:1-31:17. https://doi.org/10.4230/LIPICS.APPROX-RANDOM.2019.31
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2019 | Journal Article | LibreCat-ID: 13558 |
Gharibian, S., & Yirka, J. (2019). The complexity of simulating local measurements on quantum systems. Quantum, 3, 189. https://doi.org/10.22331/q-2019-09-30-189
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2019 | Conference Paper | LibreCat-ID: 9913 |
Ahmed, Q. A., Wiersema, T., & Platzner, M. (2019). Proof-Carrying Hardware Versus the Stealthy Malicious LUT Hardware Trojan. In C. Hochberger, B. Nelson, A. Koch, R. Woods, & P. Diniz (Eds.), Applied Reconfigurable Computing (Vol. 11444, pp. 127–136). Springer International Publishing. https://doi.org/10.1007/978-3-030-17227-5_10
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2019 | Bachelorsthesis | LibreCat-ID: 45231
N., N. (2019). Conception of a digital Sales Bonus System based on Blockchain Technology.
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2019 | Conference Paper | LibreCat-ID: 14898
Schubert, P., Leer, R., Hermann, B., & Bodden, E. (2019). Know your analysis: how instrumentation aids understanding static analysis. Proceedings of the 8th ACM SIGPLAN International Workshop on State Of the Art in Program Analysis - SOAP 2019. https://doi.org/10.1145/3315568.3329965
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2019 | Mastersthesis | LibreCat-ID: 15874 |
Lienen, C. (n.d.). Implementing a Real-time System on a Platform FPGA operated with ReconOS. Universität Paderborn.
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2019 | Journal Article | LibreCat-ID: 21
Richters, D., Lass, M., Walther, A., Plessl, C., & Kühne, T. (2019). A General Algorithm to Calculate the Inverse Principal p-th Root of Symmetric Positive Definite Matrices. Communications in Computational Physics, 25(2), 564–585. https://doi.org/10.4208/cicp.OA-2018-0053
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| arXiv
2019 | Journal Article | LibreCat-ID: 12871 |
Platzner, M., & Plessl, C. (2019). FPGAs im Rechenzentrum. Informatik Spektrum. https://doi.org/10.1007/s00287-019-01187-w
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2019 | Conference Paper | LibreCat-ID: 46338
Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2019). Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm. In K. Deb, E. Goodman, C. C. A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO) (Vol. 11411, pp. 516–528). Springer International Publishing. https://doi.org/10.1007/978-3-030-12598-1_41
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2019 | Conference Paper | LibreCat-ID: 46343
Grimme, C., Kerschke, P., & Trautmann, H. (2019). Multimodality in Multi-Objective Optimization — More Boon than Bane? In K. Deb, E. Goodman, C. C. A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO) (Vol. 11411, pp. 126–138). Springer. https://doi.org/10.1007/978-3-030-12598-1_11
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2019 | Journal Article | LibreCat-ID: 46345
Kerschke, P., Hoos, H. H., Neumann, F., & Trautmann, H. (2019). Automated Algorithm Selection: Survey and Perspectives. Evolutionary Computation (ECJ), 27(1), 3–45. https://doi.org/10.1162/evco_a_00242
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| DOI
2019 | Conference Paper | LibreCat-ID: 46339
Bossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F., & Trautmann, H. (2019). Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators. In T. Friedrich, C. Doerr, & D. Arnold (Eds.), Proceedings of the 15$^th$ ACM/SIGEVO Workshop on Foundations of Genetic Algorithms (FOGA XV) (pp. 58–71). https://doi.org/10.1145/3299904.3340307
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2019 | Conference Paper | LibreCat-ID: 46337
Bossek, J., & Trautmann, H. (2019). Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In R. Battiti, M. Brunato, I. Kotsireas, & P. Pardalos (Eds.), Learning and Intelligent Optimization (Vol. 11353, pp. 215–219). Springer.
LibreCat
2019 | Journal Article | LibreCat-ID: 46344
Carnein, M., & Trautmann, H. (2019). Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms. Business and Information Systems Engineering (BISE), 61(3), 277–297.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46340
Carnein, M., Homann, L., Trautmann, H., & Vossen, G. (2019). A Recommender System Based on Omni-Channel Customer Data. Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19), 65–74.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46341
Carnein, M., & Trautmann, H. (2019). Customer Segmentation Based on Transactional Data Using Stream Clustering. Proceedings of the 23$^rd$ Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’19), 280–292.
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