Collin Leiber


Supervised Theses

  • Numerical Algorithms for Symmetric Eigenvalue Decomposition in Subspace k-means Clustering
  • Density-Based Clustering: A Robust Multi-Density Alternative to DBSCAN
  • Improving the FOSSCLU Algorithm:Optimized Parameter-search and Clustering in Non-redundant Subspaces
  • Ein nicht-parametrischer Ansatz zur Erkennung beliebiger Clusterstrukturen
  • Automated tumor detection based on routine blood tests using Artificial Neural Networks
  • Improving Non-Redundant Clustering Approaches by K-means Extensions
  • Acquiring Meaningful Data Representations by Combining Autoencoders and Hartigan's Dip Test
  • Parameterfreies nicht-redundantes Clustering mithilfe des Dip-Tests
  • Self-Supervised Deep Clustering for Tabular Data
  • Design and Implementation of a Database with Web Interface for Side Effects of Immunotherapies
  • Evaluation of Density Based Mode Seeking
  • MDL-based Parameter Selection for Subspace and Non-Redundant Clustering
  • Empirical Assessment of Insurance Data Generation through GANs
  • Finding Consensus among Non-Redundant Clustering Algorithms
  • Informationsextraktion aus Einverständniserklärungen von klinischen Studien mittels Natural Language Processing und Maschinellem Lernen
  • Deep Learning-based Forensic Age Estimation from CT Images
  • Eine Prognose der COVID-19-Fallzahlen in Deutschland durch Neuronale Netze basierend auf Veränderungen der Mobilität
  • Minimal Description Length Principle for Parameter-free Motif Detection in Time Series Data
  • k-SubMix: Clustering on mixed-type data in optimal Subspaces
  • Subspace Clustering nicht-konvexer Strukturen durch Micro-Cluster Graphoptimierung
  • A Survey of Unimodality Tests and their Potential in Clustering Environments
  • Uncertainty Quantification in Deep Learning-Based Forensic Age Estimation
  • Deep Density-Based Clustering using Contrastive Learning
  • Building Decision Trees using Hartigans Dip-Test of Unimodality
  • A KNN-Based Deep Density Encoder for Clustering Analysis