20 citations · 158 across the 42 of their papers we have counts for
4 papers · 1 filter
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…
A Repository for Formal Contexts
Tom Hanika, Robert Jäschke
Data is always at the center of the theoretical development and investigation of the applicability of formal concept analysis. It is therefore not surprising that a large number of…
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…
The Geometric Structure of Topic Models
Johannes Hirth, Tom Hanika
Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics.…