activity
20142022
most citedUncovering structure-property relationships of materials by subgroup discovery

122 citations · 122 across the 4 of their papers we have counts for

collaborators

10 papers

cs.LG2024

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…

cs.LG2024

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…

cs.CL2023

Understanding and Mitigating Classification Errors Through Interpretable Token Patterns

Michael A. Hedderich, Jonas Fischer, Dietrich Klakow +1

State-of-the-art NLP methods achieve human-like performance on many tasks, but make errors nevertheless. Characterizing these errors in easily interpretable terms gives insight int…

cs.CL20231 cited

Towards Concept-Aware Large Language Models

Chen Shani, Jilles Vreeken, Dafna Shahaf

Concepts play a pivotal role in various human cognitive functions, including learning, reasoning and communication. However, there is very little work on endowing machines with the…

cs.LG20233 cited

Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent

Sebastian Dalleiger, Jilles Vreeken

Addressing the interpretability problem of NMF on Boolean data, Boolean Matrix Factorization (BMF) uses Boolean algebra to decompose the input into low-rank Boolean factor matrices…

cs.LG20231 cited

Preserving local densities in low-dimensional embeddings

Jonas Fischer, Rebekka Burkholz, Jilles Vreeken

Low-dimensional embeddings and visualizations are an indispensable tool for analysis of high-dimensional data. State-of-the-art methods, such as tSNE and UMAP, excel in unveiling l…