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5933 Publications


2014 | Journal Article | LibreCat-ID: 10296
Shaker, A., & Hüllermeier, E. (2014). Survival analysis on data streams: Analyzing temporal events in dynamically changing environments. Applied Mathematics and Computer Science, 24(1), 199–212.
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2014 | Journal Article | LibreCat-ID: 10297
Hoffmann, F., Hüllermeier, E., & Kroll, A. (2014). Ausgewählte Beiträge des GMA-Fachausschusses 5.14. Computational Intelligence Automatisierungstechnik, 62(10), 685–686.
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2014 | Journal Article | LibreCat-ID: 10298
Calders, T., Esposito, F., Hüllermeier, E., & Meo, R. (2014). Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track. Data Min. Knowledge Discovery, 28(5–6), 1129–1133.
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2014 | Journal Article | LibreCat-ID: 10299
Henzgen, S., Strickert, M., & Hüllermeier, E. (2014). Visualization of evolving fuzzy rule-based systems. Evolving Systems, 5(3), 175–191.
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2014 | Journal Article | LibreCat-ID: 10308
Hüllermeier, E. (2014). Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization. Int. J. Approx. Reasoning, 55(7), 1519–1534.
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2014 | Journal Article | LibreCat-ID: 10309
Hüllermeier, E. (2014). Rejoinder on "Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization. Int. J. Approx. Reasoning, 55(7), 1609–1613.
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2014 | Journal Article | LibreCat-ID: 10310
Strickert, M., Bunte, K., Schleif, F.-M., & Hüllermeier, E. (2014). Correlation-based embedding of pairwise score data. Neurocomputing, 141, 97–109.
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2014 | Journal Article | LibreCat-ID: 10311
Senge, R., Bösner, S., Dembczynski, K., Haasenritter, J., Hirsch, O., Donner-Banzhoff, N., & Hüllermeier, E. (2014). Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty. Information Sciences, 255, 16–29.
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2014 | Journal Article | LibreCat-ID: 10312
Mernberger, M., Moog, M., Stork, S., Zauner, S., Maier, U. G., & Hüllermeier, E. (2014). Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances. J. Bioinformatics and Computational Biology, 12(1).
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2014 | Journal Article | LibreCat-ID: 10313
Calders, T., Esposito, F., Hüllermeier, E., & Meo, R. (2014). Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track. Machine Learning, 97(1–2), 1–3.
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2014 | Journal Article | LibreCat-ID: 10314
Busa-Fekete, R., Szörényi, B., Weng, P., Cheng, W., & Hüllermeier, E. (2014). Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm. Machine Learning, 97(3), 327–351.
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2014 | Journal Article | LibreCat-ID: 10315
Montanés, E., Senge, R., Barranquero, J., Quevedo, J. R., Del Coz, J. J., & Hüllermeier, E. (2014). Dependent binary relevance models for multi-label classification. Pattern Recognition, 47(3), 1494–1508.
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2014 | Journal Article | LibreCat-ID: 10316
Krempl, G., Zliobaite, I., Brzezinski, D., Hüllermeier, E., Last, M., Lemaire, V., … Stefanowski, J. (2014). Open challenges for data stream mining research. SIGKDD Explorations, 16(1), 1–10.
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2014 | Journal Article | LibreCat-ID: 10317
Krotzky, T., Fober, T., Hüllermeier, E., & Klebe, G. (2014). Extended Graph-Based Models for Enhanced Similarity Search in Cavbase. IEEE/ACM Trans. Comput. Biology Bioinform., 11(5), 878–890.
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2014 | Journal Article | LibreCat-ID: 10318
Stock, M., Fober, T., Hüllermeier, E., Glinca, S., Klebe, G., Pahikkala, T., … Wageman, W. (2014). Identification of Functionally Releated Enzymes by Learning to Rank Methods. IEEE/ACM Trans. Comput. Biology Bioinform., 11(6), 1157–1169.
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2014 | Journal Article | LibreCat-ID: 1375
Beister, F., Dräxler, M., Aelken, J., & Karl, H. (2014). Power model design for ICT systems – A generic approach. Computer Communications, 50, 77–85. https://doi.org/10.1016/j.comcom.2014.02.007
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2014 | Book Chapter | LibreCat-ID: 46381
Kerschke, P., Preuss, M., Hernández, C., Schütze, O., Sun, J.-Q., Grimme, C., Rudolph, G., Bischl, B., & Trautmann, H. (2014). Cell Mapping Techniques for Exploratory Landscape Analysis. In A.-A. Tantar, E. Tantar, J.-Q. Sun, W. Zhang, Q. Ding, O. Schütze, M. T. M. Emmerich, P. Legrand, M. P. Del, & C. C. A. Coello (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (Vol. 288, pp. 115–131). Springer International Publishing. https://doi.org/10.1007/978-3-319-07494-8_9
LibreCat | DOI
 

2014 | Book Chapter | LibreCat-ID: 46382
Rudolph, G., Schütze, O., Grimme, C., & Trautmann, H. (2014). A Multiobjective Evolutionary Algorithm Guided by Averaged Hausdorff Distance to Aspiration Sets. In A. Tantar, E. Tantar, J. Sun, W. Zhang, Q. Ding, O. Schütze, M. Emmerich, P. Legrand, M. P. Del, & C. C. Coello (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (Vol. 288, pp. 261–273). Springer International Publishing. https://doi.org/10.1007/978-3-319-07494-8_18
LibreCat | DOI
 

2014 | Conference Paper | LibreCat-ID: 46383
Rudolph, G., Grimme, C., Schütze, O., & Trautmann, H. (2014). An Aspiration Set EMOA Based on Averaged Hausdorff Distances. Proceedings of the Learning and Intelligent OptimizatioN Conference (LION 8), 8426, 153–156.
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2014 | Conference Paper | LibreCat-ID: 46384
Wessing, S., Preuss, M., & Trautmann, H. (2014). Stopping Criteria for Multimodal Optimization. In T. Bartz-Beielstein, J. Branke, B. Filipic, & J. Smith (Eds.), Proceedings of the Parallel Problem Solving from Nature — PPSN XIII (Vol. 8672, pp. 141–150). Springer. https://doi.org/10.1007/978-3-319-10762-2_14
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