10 citations · 11 across the 2 of their papers we have counts for
5 papers
What's Wrong with Deep Learning in Tree Search for Combinatorial Optimization
Maximilian Böther, Otto Kißig, Martin Taraz +3
Combinatorial optimization lies at the core of many real-world problems. Especially since the rise of graph neural networks (GNNs), the deep learning community has been developing…
Law Smells: Defining and Detecting Problematic Patterns in Legal Drafting
Corinna Coupette, Dirk Hartung, Janis Beckedorf +2
Building on the computer science concept of code smells, we initiate the study of law smells, i.e., patterns in legal texts that pose threats to the comprehensibility and maintaina…
Learning Languages with Decidable Hypotheses
Julian Berger, Maximilian Böther, Vanja Doskoč +9
In language learning in the limit, the most common type of hypothesis is to give an enumerator for a language. This so-called -index allows for naming arbitrary computably enume…
Maps for Learning Indexable Classes
Julian Berger, Maximilian Böther, Vanja Doskoč +9
We study learning of indexed families from positive data where a learner can freely choose a hypothesis space (with uniformly decidable membership) comprising at least the language…
A Strategic Routing Framework and Algorithms for Computing Alternative Paths
Thomas Bläsius, Maximilian Böther, Philipp Fischbeck +9
Traditional navigation services find the fastest route for a single driver. Though always using the fastest route seems desirable for every individual, selfish behavior can have un…