3 citations · 3 across the 4 of their papers we have counts for
4 papers
Rises for Measuring Local Distributivity in Lattices
Mohammad Abdulla, Tobias Hille, Dominik Dürrschnabel +1
Distributivity is a well-established and extensively studied notion in lattice theory. In the context of data analysis, particularly within Formal Concept Analysis (FCA), lattices…
What is the dimension of your binary data? -- and how to compute it quickly
Tom Hanika, Tobias Hille
Dimensionality is an important aspect for analyzing and understanding (high-dimensional) data. In their 2006 ICDM paper Tatti et al. answered the question for a (interpretable) dim…
Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research
Tobias Hille, Maximilian Stubbemann, Tom Hanika
Difficulties in replication and reproducibility of empirical evidences in machine learning research have become a prominent topic in recent years. Ensuring that machine learning re…
Selecting Features by their Resilience to the Curse of Dimensionality
Maximilian Stubbemann, Tobias Hille, Tom Hanika
Real-world datasets are often of high dimension and effected by the curse of dimensionality. This hinders their comprehensibility and interpretability. To reduce the complexity fea…