2 papers
cs.LG2020
Learning Choice Functions via Pareto-Embeddings
Karlson Pfannschmidt, Eyke Hüllermeier
We consider the problem of learning to choose from a given set of objects, where each object is represented by a feature vector. Traditional approaches in choice modelling are main…
stat.ML2018
Deep Architectures for Learning Context-dependent Ranking Functions
Karlson Pfannschmidt, Pritha Gupta, Eyke Hüllermeier
Object ranking is an important problem in the realm of preference learning. On the basis of training data in the form of a set of rankings of objects, which are typically represent…