Search Results - "Hullermeier, Eyke"

Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods by Hüllermeier, Eyke, Waegeman, Willem

“…The notion of uncertainty is of major importance in machine learning and constitutes a key element of machine learning methodology. In line with the…”
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Safe Bayesian Optimization for Data-Driven Power Electronics Control Design in Microgrids: From Simulations to Real-World Experiments by Weber, Daniel, Heid, Stefan, Bode, Henrik, Lange, Jarren H., Hullermeier, Eyke, Wallscheid, Oliver

“…Micro- and smart grids (MSG) play an important role both for integrating renewable energy sources in electricity grids and for providing power supply in remote…”
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Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization by Huellermeier, Eyke

“…Methods for analyzing or learning from “fuzzy data” have attracted increasing attention in recent years. In many cases, however, existing methods (for precise,…”
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Combining instance-based learning and logistic regression for multilabel classification by Cheng, Weiwei, Hüllermeier, Eyke

“…Multilabel classification is an extension of conventional classification in which a single instance can be associated with multiple labels. Recent research has…”
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How to measure uncertainty in uncertainty sampling for active learning by Nguyen, Vu-Linh, Shaker, Mohammad Hossein, Hüllermeier, Eyke

“…Various strategies for active learning have been proposed in the machine learning literature. In uncertainty sampling, which is among the most popular…”
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An Extensive Analysis of Different Approaches to Driver Gaze Classification by Camberg, Simone, Hullermeier, Eyke

“…Driver Monitoring Systems (DMS) enable Intelligent Vehicles to capture the in-cabin scene and help determine the driver's level of attention and ability to…”
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Conformal Prediction Intervals for Remaining Useful Lifetime Estimation by Javanmardi, Alireza, Hüllermeier, Eyke

“…The main objective of Prognostics and Health Management is to estimate the Remaining Useful Lifetime (RUL), namely, the time that a system or a piece of…”
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Preferences in AI: An overview by Domshlak, Carmel, Hüllermeier, Eyke, Kaci, Souhila, Prade, Henri

“…This editorial of the special issue “Representing, Processing, and Learning Preferences: Theoretical and Practical Challenges” surveys past and ongoing…”
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Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons by Bustince, H., Pagola, M., Mesiar, R., Hullermeier, E., Herrera, F.

“…In this paper, we propose new aggregation functions for the pairwise comparison of alternatives in fuzzy preference modeling. More specifically, we introduce…”
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TSK-Streams: learning TSK fuzzy systems for regression on data streams by Shaker, Ammar, Hüllermeier, Eyke

“…The problem of adaptive learning from evolving and possibly non-stationary data streams has attracted a lot of interest in machine learning in the recent past,…”
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Multilabel classification via calibrated label ranking by Fürnkranz, Johannes, Hüllermeier, Eyke, Loza Mencía, Eneldo, Brinker, Klaus

“…Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label…”
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Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures by Hullermeier, E., Rifqi, M., Henzgen, S., Senge, R.

“…In this paper, we introduce a fuzzy extension of a class of measures to compare clustering structures, namely, measures that are based on the number of…”
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Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies—part II by Hüllermeier, Eyke, Słowiński, Roman

“…This article elaborates on the connection between multiple criteria decision aiding (MCDA) and preference learning (PL), two research fields with different…”
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On testing transitivity in online preference learning by Haddenhorst, Björn, Bengs, Viktor, Hüllermeier, Eyke

“…The efficiency of state-of-the-art algorithms for the dueling bandits problem is essentially due to a clever exploitation of (stochastic) transitivity…”
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AutoML for Multi-Label Classification: Overview and Empirical Evaluation by Wever, Marcel, Tornede, Alexander, Mohr, Felix, Hullermeier, Eyke

“…Automated machine learning (AutoML) supports the algorithmic construction and data-specific customization of machine learning pipelines, including the…”
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Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies–part I by Hüllermeier, Eyke, Słowiński, Roman

“…Multiple criteria decision aiding (MCDA) and preference learning (PL) are established research fields, which have different roots, developed in different…”
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Efficient set-valued prediction in multi-class classification by Mortier, Thomas, Wydmuch, Marek, Dembczyński, Krzysztof, Hüllermeier, Eyke, Waegeman, Willem

“…In cases of uncertainty, a multi-class classifier preferably returns a set of candidate classes instead of predicting a single class label with little…”
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Fast Fuzzy Pattern Tree Learning for Classification by Senge, Robin, Hullermeier, Eyke

“…Fuzzy pattern trees have recently been introduced as a novel type of fuzzy system, specifically with regard to the modeling of classification functions in…”
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Lexicographic preferences for predictive modeling of human decision making: A new machine learning method with an application in accounting by Bräuning, Michael, Hüllermeier, Eyke, Keller, Tobias, Glaum, Martin

“…•We highlight cognitive plausibility of lexicographic preferences in human decisions.•Novel learning algorithm for inducing generalized lexicographic…”
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Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistance prediction by Heider, Dominik, Senge, Robin, Cheng, Weiwei, Hüllermeier, Eyke

“…Antiretroviral treatment regimens can sufficiently suppress viral replication in human immunodeficiency virus (HIV)-infected patients and prevent the…”
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