Ministry of Planning - Schulze, Max

Interview with Sebastian Luft - Luft, Sebastian

How to Think about Your Dissertation Paper - Luft, Sebastian

Zu Wort kommen: Narration als Zugang zum Thema Inklusion - Kammeyer, Katharina; Roebben, Bert; Baumert, Britta

Kinder feiern Ramadan: Ein interreligiöses Praxisbuch für den Kindergarten - Kammeyer, Katharina; Kamcili-Yildiz, Naciye; Tombrink , Claudia; Biricik, Senay

Inklusive Wege des Umgangs mit Heterogenität im Religionsunterricht. Wahrnehmungen von Religionslehrerinnen und -lehrern, bildungstheoretische Reflexionen und Herausforderungen für das Studium - Kammeyer, Katharina (Inklusion im Studium Evangelische Theologie. Grundlagen und Perspektiven mit einem Schwerpunkt im Bereich Sinnesbehinderungen)

Inklusion als Narration. Einleitende Gedanken - Kammeyer, Katharina (Zu Wort kommen. Narration als Zugang zum Thema Inklusion)

Teachers’ perspectives on Theologizing and diversity in classroom teaching - Kammeyer, Katharina (Children‘s voices. Theological, philosophical and spiritual perspectives)

Reformiertes Bekennen heute. Bekenntnistexte der Gegenwart von Belhar bis Kappel

Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement - Bossek, Jakob; Bischl, Bernd; Wagner, Tobias; Rudolph, Günter (Proceedings of the Genetic and Evolutionary Computation Conference)
The majority of algorithms can be controlled or adjusted by parameters. Their values can substantially affect the algorithms’ performance. Since the manual exploration of the parameter space is tedious – even for few parameters – several automatic procedures for parameter tuning have been proposed. Recent approaches also take into account some characteristic properties of the problem instances, frequently termed instance features. Our contribution is the proposal of a novel concept for feature-based algorithm parameter tuning, which applies an approximating surrogate model for learning the continuous feature-parameter mapping. To accomplish this, we learn a joint model of the algorithm performance based on both the algorithm parameters and the instance features. The required data is gathered using a recently proposed acquisition function for model refinement in surrogate-based optimization: the profile expected improvement. This function provides an avenue for maximizing the information required for the feature-parameter mapping, i.e., the mapping from instance features to the corresponding optimal algorithm parameters. The approach is validated by applying the tuner to exemplary evolutionary algorithms and problems, for which theoretically grounded or heuristically determined feature-parameter mappings are available.
Keywords: evolutionary algorithms; model-based optimization; parameter tuning

Stars als Erinnerungsanker und Generationenmarker. Medienöffentliche Figuren als Identifikations- und Projektionsflächen in inter- und intragenerationellen Diskursen. - Jacke, Christoph (Hot Stuff. Gender, Popkultur und Generationalität in West- und Osteuropa nach 1945.)

So Far...From Now On # 4. Kolumne. - Jacke, Christoph (Die Aufhebung)

Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle - Meisel, Stephan; Grimme, Christian; Bossek, Jakob; Wölck, Martin; Rudolph, Günter; Trautmann, Heike (Proceedings of the Genetic and Evolutionary Computation Conference)
We evaluate the performance of a multi-objective evolutionary algorithm on a class of dynamic routing problems with a single vehicle. In particular we focus on relating algorithmic performance to the most prominent characteristics of problem instances. The routing problem considers two types of customers: mandatory customers must be visited whereas optional customers do not necessarily have to be visited. Moreover, mandatory customers are known prior to the start of the tour whereas optional customers request for service at later points in time with the vehicle already being on its way. The multi-objective optimization problem then results as maximizing the number of visited customers while simultaneously minimizing total travel time. As an a-posteriori evaluation tool, the evolutionary algorithm aims at approximating the related Pareto set for specifically designed benchmarking instances differing in terms of number of customers, geographical layout, fraction of mandatory customers, and request times of optional customers. Conceptional and experimental comparisons to online heuristic procedures are provided.
Keywords: combinatorial optimization; metaheuristics; multi-objective optimization; online algorithms; transportation

Zur Not auch die ZDF-Hitparade. Ein Gespräch über Popmusik und Fernsehen in Deutschland. - Jacke, Christoph; Kavka, Markus (Popkultur und Fernsehen. Historische und ästhetische Berührungspunkte.)

Gedächtnis und Erinnerung. - Jacke, Christoph; Zierold, Martin (Handbuch Cultural Studies und Medienanalyse.)

So Far...From Now On # 3. Kolumne. - Jacke, Christoph (Die Aufhebung)

Open Space. Der Raum als Möglichkeit.

Endliche Automaten und formale Sprachen - Scholle, Oliver (Informatik 2)

Lineare Datenstrukturen - Scholle, Oliver (Informatik 2)

Schauanordnungen des Kleinen in Kunst und Literatur. - Autsch, Sabiene; Öhlschläger, Claudia (kritische berichte. Zeitschrift für Kunst- und Kulturwissenschaften.)