1.7k citations · 2.1k across the 113 of their papers we have counts for
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TSK-Streams: Learning TSK Fuzzy Systems on Data Streams
Ammar Shaker, Eyke Hüllermeier
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, and also stimulated…
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods
Eyke Hüllermeier, Willem Waegeman
The notion of uncertainty is of major importance in machine learning and constitutes a key element of machine learning methodology. In line with the statistical tradition, uncertai…
Epistemic Uncertainty Sampling
Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier
Various strategies for active learning have been proposed in the machine learning literature. In uncertainty sampling, which is among the most popular approaches, the active learne…
Preselection Bandits
Viktor Bengs, Eyke Hüllermeier
In this paper, we introduce the Preselection Bandit problem, in which the learner preselects a subset of arms (choice alternatives) for a user, which then chooses the final arm fro…
Rectifying Classifier Chains for Multi-Label Classification
Robin Senge, Juan José del Coz, Eyke Hüllermeier
Classifier chains have recently been proposed as an appealing method for tackling the multi-label classification task. In addition to several empirical studies showing its state-of…
Efficient Set-Valued Prediction in Multi-Class Classification
Thomas Mortier, Marek Wydmuch, Krzysztof Dembczyński +2
In cases of uncertainty, a multi-class classifier preferably returns a set of candidate classes instead of predicting a single class label with little guarantee. More precisely, th…
Reliable Multi-label Classification: Prediction with Partial Abstention
Vu-Linh Nguyen, Eyke Hüllermeier
In contrast to conventional (single-label) classification, the setting of multilabel classification (MLC) allows an instance to belong to several classes simultaneously. Thus, inst…
Analogy-Based Preference Learning with Kernels
Mohsen Ahmadi Fahandar, Eyke Hüllermeier
Building on a specific formalization of analogical relationships of the form "A relates to B as C relates to D", we establish a connection between two important subfields of artifi…