3 citations · 5 across the 4 of their papers we have counts for
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Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
Exploiting dependencies between labels is considered to be crucial for multi-label classification. Rules are able to expose label dependencies such as implications, subsumptions or…
Learning Interpretable Rules for Multi-label Classification
Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier +1
Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels…
Analysis and Optimization of Deep Counterfactual Value Networks
Patryk Hopner, Eneldo Loza Mencía
Recently a strong poker-playing algorithm called DeepStack was published, which is able to find an approximate Nash equilibrium during gameplay by using heuristic values of future…