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D. Schäfer and E. Hüllermeier, “Preference -based reinforcement learning using dyad ranking,” in in Proceedings DPL16 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany, 2016.

I. Couso, M. Ahmadi Fahandar, and E. Hüllermeier, “Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators,” in in Proceedings DPL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016.

S. Lu and E. Hüllermeier, “Support vector classification on noisy data using fuzzy superset losses,” in in Proceedings 26th Workshop Computational Intelligence, Dortmund Germany, 2016, pp. 1–8.

D. Schäfer and E. Hüllermeier, “Plackett-Luce networks for dyad ranking,” in in Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016.

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S. Arifulina, Solving Heterogeneity for a Successful Service Market. Universität Paderborn, 2016.

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A. Macker, M. Malatyali, and F. Meyer auf der Heide, “On Competitive Algorithms for Approximations of Top-k-Position Monitoring of Distributed Streams,” in 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2016.

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S. Ester, M. Struschka, and B. Henning, “.2.3 - Direktgravimetrischer Partikelmasse-Sensor zur quasikontinuierlichen Emissionsmessung,” 2016.

S. Abshoff, P. Kling, C. Markarian, F. Meyer auf der Heide, and P. Pietrzyk, “Towards the price of leasing online,” Journal of Combinatorial Optimization, no. 4, pp. 1197--1216, 2016.

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E. Moritzer, M. Hüttner, B. Henning, and M. Webersen, “An Approach to Non-Destructive Testing of Aged Polymers,” presented at the 32nd International Conference of the Polymer Processing Society, Lyon, 2016.

E. Moritzer, M. Hüttner, B. Henning, and M. Webersen, “Molekularen Schäden auf der Spur,” Kunststoffe, no. 4, pp. 94–96, 2016.

E. Moritzer, M. Hüttner, B. Henning, and M. Webersen, “Detecting Molecular Damage,” Kunststoffe International, no. 4, pp. 43–45, 2016.

E. Moritzer, M. Hüttner, B. Henning, and M. Webersen, “Non-destructive characterization of hygrothermally aged polymers,” presented at the ANTEC 2016, Indianapolis, 2016.

E. Moritzer, M. Hüttner, B. Henning, and M. Webersen, “Ultraschallbasierte Charakterisierung von gealterten Polymeren,” in Jahresmagazin Kunststofftechnik 2016, Institut für Wissenschaftliche Veröffentlichungen, Ed. 2016, pp. 2–7.

M. Webersen, M. Hüttner, F. Bause, E. Moritzer, and B. Henning, “Zerstörungsfreie Charakterisierung des hydrothermischen Alterungsverhaltens von Polymeren,” presented at the 18. GMA/ITG-Fachtagung Sensoren und Messsysteme 2016, Nürnberg, 2016, pp. 683–688.

M. Dewender, Verifikation von Service Kompositionen mit Spin. Universität Paderborn, 2016.

P. Heinisch, Verifikation von Service Kompositionen mit Prolog. Universität Paderborn, 2016.

M. Eikel, Insider-resistent Distributed Storage Systems. Universität Paderborn, 2016.

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K. Jasinska, K. Dembczynski, R. Busa-Fekete, T. Klerx, and E. Hüllermeier, “Extreme F-measure maximization using sparse probability estimates ,” in Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA, 2016.

V. Melnikov and E. Hüllermeier, “Learning to aggregate using uninorms,  in Proceedings ECML/PKDD-2016,” in European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy, 2016, pp. 756–771.

K. Dembczynski, W. Kotlowski, W. Waegeman, R. Busa-Fekete, and E. Hüllermeier, “Consistency of probalistic classifier trees,” in In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy, 2016, pp. 511–526.

A. Shabani, A. Paul, R. Platon, and E. Hüllermeier, “Predicting the electricity consumption of buildings: An improved CBR approach,” in In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA, 2016, pp. 356–369.

K. Pfannschmidt, E. Hüllermeier, S. Held, and R. Neiger, “Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts,” in In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, 2016, pp. 450–461.

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S. Lu and E. Hüllermeier, “Support vector classification on noisy data using fuzzy supersets losses,” in Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing, 2016, pp. 1–8.

D. Schäfer and E. Hüllermeier, “Plackett-Luce networks for dyad ranking,” in In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016.

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M. Riemenschneider, R. Senge, U. Neumann, E. Hüllermeier, and D. Heider, “Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification,” BioData Mining, vol. 9, no. 10, 2016.

M. Herlich, N. Bredenbals, and H. Karl, “Delayed (de-)activation in servers with a sleep mode,” Sustainable Computing: Informatics and Systems, vol. 10, pp. 48–55, 2016.

P. Adelt, B. Koppelmann, W. Müller, M. Becker, B. Kleinjohann, and C. Scheytt, “Fast Dynamic Fault Injection for Virtual Microcontroller Platforms,”10.1109/VLSI-SoC.2016.7753545__2016, doi:10.1109/VLSI-SoC.2016.7753545 .

Y. Mao, K. Schmalz, C. Scheytt, and E. Shiju, “An all-transmission-line 220 GHz differential LNA in SiGe BiCMOS,”10.1109/RFIT.2016.7578132__2016, doi:10.1109/RFIT.2016.7578132 .

S. Abughannam, L. Wu, W. Müller, C. Scheytt, W. Ecker, and C. Novello, “Fault Injection and Mixed-Level Simulation for Analog Circuits - A Case Study,” 2016.

F. Nava, D. Genschow, and C. Scheytt, “Obstacle detection using a miniaturized radar sensor operating at 120GHz ISM band,” 2016.

A. R. Javed, C. Scheytt, and U. Von der Ahe, “Linear ultra-broadband NPN-only analog correlator at 33 Gbps in 130nm SiGe BiCMOS technology,” 10.1109/BCTM.2016.7738962__2016, doi: 10.1109/BCTM.2016.7738962 .

J. Jatzkowski, P. Adelt, and A. Rettberg, “Hierarchical Scheduling for Plug-and-Produce,” 10.1016/j.protcy.2016.08.031__in 3rd International Conference on System-integrated Intelligence: New Challenges for Product and Production Engineering, 2016, pp. 227–234, doi: 10.1016/j.protcy.2016.08.031 .

F. Nava, C. Scheytt, T. Zwick, M. Pauli, B. Goettel, and W. Winkler, “Ultra-compact 122GHz Radar Sensor for Autonomous Aircrafts,” 10.1016/j.protcy.2016.08.051__2016, doi: 10.1016/j.protcy.2016.08.051 .

J. Böcker, “Some reflections on electromagnetic force in matter,”10.1109/speedam.2016.7525880__presented at the SPEEDAM, Capri, Italy, 2016, doi:10.1109/speedam.2016.7525880 .

K. S. C. Stille and J. Böcker, “Local demand response and load planning system for intelligent domestic appliances,”10.1109/icrera.2015.7418638__2016, doi:10.1109/icrera.2015.7418638 .

K. S. C. Stille, J. Böcker, N. Fröhleke, R. Bettentrup, and I. Kaiser, “Integration of home photovoltaic generation into electricity tariff for load optimization,”10.1109/sgcf.2016.7492441__2016, doi:10.1109/sgcf.2016.7492441 .

K. S. C. Stille, J. Böcker, N. Fröhleke, R. Bettentrup, and I. Kaiser, “Local grid load coordination for load-shiftable domestic appliances in a variable-tariff environment,”10.1109/epe.2016.7695583__2016, doi:10.1109/epe.2016.7695583 .

K. S. C. Stille, J. Böcker, N. Fröhleke, R. Bettentrup, and I. Kaiser, “Supervisional load optimization for households with intelligent domestic appliances,”10.1109/cpe.2016.7544176__2016, doi:10.1109/cpe.2016.7544176 .

O. Wallscheid, T. Huber, W. Peters, and J. Böcker, “A Critical Review of Techniques to Determine the Magnet Temperature of Permanent Magnet Synchronous Motors under Real-time Conditions,” EPE Journal, no. 25, pp. 1–10, 2016.

O. Wallscheid, U. Ammann, and J. Böcker, “Real-time capable model predictive control of permanent magnet synchronous motors using particle swarm optimisation,” in PCIM Europe 2016; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, 2016, pp. 1–8.

M. Paradkar and J. Böcker, “D analytical model for estimation of eddy current loss in the magnets of IPM machines considering the reaction field of the induced eddy currents,”10.1109/iemdc.2015.7409198__2016, doi:10.1109/iemdc.2015.7409198 .

T. Huber, W. Peters, and J. Böcker, “Voltage controller for flux weakening operation of interior permanent magnet synchronous motor in automotive traction applications,”10.1109/iemdc.2015.7409195__2016, doi:10.1109/iemdc.2015.7409195 .

M. Paradkar and J. Böcker, “Analysis of eddy current losses in the stator windings of IPM machines in electric and hybrid electric vehicle applications,”10.1049/cp.2016.0320__2016, doi:10.1049/cp.2016.0320 .

K. Peter, J. Böcker, F. Mink, and S. Beineke, “Comparison of quarter-wave with half-wave symmetrical pulse patterns applied in electrical high-speed drives,”10.1049/cp.2016.0358__2016, doi:10.1049/cp.2016.0358 .

C. Schulte, K. Peter, J. Böcker, and M. Leuer, “Comparison of Optimized Pulse Patterns with Direct Model Predictive Control Using Co-Simulation,”10.1049/cp.2016.0331__2016, doi:10.1049/cp.2016.0331 .

K. Peter, S. Hanke, F. Mink, and J. Böcker, “Inverter loss management for an electrical high-speed drive system,”10.1109/epe.2016.7695587__2016, doi:10.1109/epe.2016.7695587 .

M. Ott and J. Böcker, “Sensitivity analysis on production tolerances for electric drive systems in automotive application,”10.1109/epe.2016.7695392__2016, doi:10.1109/epe.2016.7695392 .

M. Leuer, M. Lönneker, and J. Böcker, “Model predictive control strategy for multi-phase thyristor matrix converters — Advantages, problems and solutions,”10.1109/epe.2016.7695350__2016, doi:10.1109/epe.2016.7695350 .

S. Bolte, N. Fröhleke, and J. Böcker, “Comparison of the performance of gallium nitride (GaN) transistors in a totem-pole power factor controlled (PFC) rectifier,”10.1109/intlec.2016.7749113__2016, doi:10.1109/intlec.2016.7749113 .

T. Vogt, R. Pahl, N. Fröhleke, and J. Böcker, “Determination of storage loss characteristics with reasonable measurement and calculation effort,”10.1109/epe.2016.7695689__2016, doi:10.1109/epe.2016.7695689 .