TY - JOUR AB - We investigate optical microresonators consisting of either one or two coupled rectangular strips between upper and lower slab waveguides. The cavities are evanescently excited under oblique angles by thin-film guided, in-plane unguided waves supported by one of the slab waveguides. Beyond a specific incidence angle, losses are fully suppressed. The interaction between the guided mode of the cavity-strip and the incoming slab modes leads to resonant behavior for specific incidence angles and gaps. For a single cavity, at resonance, the input power is equally split among each of the four output ports, while for two cavities an add-drop filter can be realized that, at resonance, routes the incoming power completely to the forward drop waveguide via the cavity. For both applications, the strength of the interaction is controlled by the gaps between cavities and waveguides. AU - Ebers, Lena AU - Hammer, Manfred AU - Berkemeier, Manuel B. AU - Menzel, Alexander AU - Förstner, Jens ID - 14990 JF - OSA Continuum KW - tet_topic_waveguides SN - 2578-7519 TI - Coupled microstrip-cavities under oblique incidence of semi-guided waves: a lossless integrated optical add-drop filter VL - 2 ER - TY - JOUR AU - Couso, Ines AU - Borgelt, Christian AU - Hüllermeier, Eyke AU - Kruse, Rudolf ID - 15001 JF - IEEE Computational Intelligence Magazine SN - 1556-603X TI - Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning ER - TY - JOUR AB - Many problem settings in machine learning are concerned with the simultaneous prediction of multiple target variables of diverse type. Amongst others, such problem settings arise in multivariate regression, multi-label classification, multi-task learning, dyadic prediction, zero-shot learning, network inference, and matrix completion. These subfields of machine learning are typically studied in isolation, without highlighting or exploring important relationships. In this paper, we present a unifying view on what we call multi-target prediction (MTP) problems and methods. First, we formally discuss commonalities and differences between existing MTP problems. To this end, we introduce a general framework that covers the above subfields as special cases. As a second contribution, we provide a structured overview of MTP methods. This is accomplished by identifying a number of key properties, which distinguish such methods and determine their suitability for different types of problems. Finally, we also discuss a few challenges for future research. AU - Waegeman, Willem AU - Dembczynski, Krzysztof AU - Hüllermeier, Eyke ID - 15002 IS - 2 JF - Data Mining and Knowledge Discovery SN - 1573-756X TI - Multi-target prediction: a unifying view on problems and methods VL - 33 ER - TY - CONF AU - Mortier, Thomas AU - Wydmuch, Marek AU - Dembczynski, Krzysztof AU - Hüllermeier, Eyke AU - Waegeman, Willem ID - 15003 T2 - Proceedings of the 31st Benelux Conference on Artificial Intelligence {(BNAIC} 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019 TI - Set-Valued Prediction in Multi-Class Classification ER - TY - CHAP AU - Ahmadi Fahandar, Mohsen AU - Hüllermeier, Eyke ID - 15004 SN - 0302-9743 T2 - Discovery Science TI - Feature Selection for Analogy-Based Learning to Rank ER - TY - CHAP AU - Ahmadi Fahandar, Mohsen AU - Hüllermeier, Eyke ID - 15005 SN - 0302-9743 T2 - KI 2019: Advances in Artificial Intelligence TI - Analogy-Based Preference Learning with Kernels ER - TY - CHAP AU - Nguyen, Vu-Linh AU - Destercke, Sébastien AU - Hüllermeier, Eyke ID - 15006 SN - 0302-9743 T2 - Discovery Science TI - Epistemic Uncertainty Sampling ER - TY - CONF AU - Melnikov, Vitaly AU - Hüllermeier, Eyke ID - 15007 T2 - Proceedings ACML, Asian Conference on Machine Learning (Proceedings of Machine Learning Research, 101) TI - Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA ER - TY - CONF AU - Epple, Nico AU - Dari, Simone AU - Drees, Ludwig AU - Protschky, Valentin AU - Riener, Andreas ID - 15009 SN - 9781728105604 T2 - 2019 IEEE Intelligent Vehicles Symposium (IV) TI - Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries ER - TY - CONF AU - Tornede, Alexander AU - Wever, Marcel Dominik AU - Hüllermeier, Eyke ED - Hoffmann, Frank ED - Hüllermeier, Eyke ED - Mikut, Ralf ID - 15011 SN - 978-3-7315-0979-0 T2 - Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019 TI - Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking ER -