1 citations · 3 across the 21 of their papers we have counts for
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From your Block to our Block: How to Find Shared Structure between Stochastic Block Models over Multiple Graphs
Iiro Kumpulainen, Sebastian Dalleiger, Jilles Vreeken +1
Stochastic Block Models (SBMs) are a popular approach to modeling single real-world graphs. The key idea of SBMs is to partition the vertices of the graph into blocks with similar…
Neuro-Symbolic Rule Lists
Sascha Xu, Nils Philipp Walter, Jilles Vreeken
Machine learning models deployed in sensitive areas such as healthcare must be interpretable to ensure accountability and fairness. Rule lists (if Age < 35 Priors > 0 then…
Federated Binary Matrix Factorization using Proximal Optimization
Sebastian Dalleiger, Jilles Vreeken, Michael Kamp
Identifying informative components in binary data is an essential task in many research areas, including life sciences, social sciences, and recommendation systems. Boolean matrix…
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective
Nils Philipp Walter, Linara Adilova, Jilles Vreeken +1
Flatness of the loss surface not only correlates positively with generalization, but is also related to adversarial robustness since perturbations of inputs relate non-linearly to…
Learning Exceptional Subgroups by End-to-End Maximizing KL-divergence
Sascha Xu, Nils Philipp Walter, Janis Kalofolias +1
Finding and describing sub-populations that are exceptional regarding a target property has important applications in many scientific disciplines, from identifying disadvantaged de…
Succinct Interaction-Aware Explanations
Sascha Xu, Joscha Cüppers, Jilles Vreeken
SHAP is a popular approach to explain black-box models by revealing the importance of individual features. As it ignores feature interactions, SHAP explanations can be confusing up…