Testing a Simulated Annealing Algorithm in a Classification Problem. - Karsten Luebke; Claus Weihs (SAGA, 2003)

KMC/EDAM: A New Approach for the Visualization of K-Means Clustering Results. - Nils Raabe; Karsten Luebke; Claus Weihs (GfKl, 2004)

Different Subspace Classification. - Gero Szepannek; Karsten Luebke (GfKl, 2004)

Generation of prediction optimal projection on latent factors by a stochastic search algorithm. - Karsten Luebke; Claus Weihs (Comput. Stat. Data Anal., 2004)

Understanding Patterns with Different Subspace Classification. - Gero Szepannek; Karsten Luebke; Claus Weihs (MLDM, 2005)

Improving feature extraction by replacing the Fisher criterion by an upper error bound. - Karsten Luebke; Claus Weihs (Pattern Recognit., 2005)

klaR Analyzing German Business Cycles. - Claus Weihs; Uwe Ligges; Karsten Luebke; Nils Raabe (Data Analysis and Decision Support, 2005)

Localized Linear Discriminant Analysis. - Irina Czogiel; Karsten Luebke; Marc Zentgraf; Claus Weihs (GfKl, 2006)

Local Models in Register Classification by Timbre. - Claus Weihs; Gero Szepannek; Uwe Ligges; Karsten Luebke; Nils Raabe (Data Science and Classification, 2006)

Linear dimension reduction in classification: adaptive procedure for optimum results. - Karsten Luebke; Claus Weihs (Adv. Data Anal. Classif., 2011)

Firm-Specific Determinants on Dividend Changes: Insights from Data Mining. - Karsten Luebke; Joachim Rojahn (ECDA, 2014)

Facing the Challenges of Developing Fair Risk Scoring Models. - Gero Szepannek; Karsten Luebke (Frontiers Artif. Intell., 2021)

Teaching Machine Learning with mlr3 using Shiny. - Gero Szepannek; Laurens Martin Tetzlaff; Alexander Frahm; Karsten Lübke (Teaching ML, 2022)

Causality in statistics and data science education. - Kevin Cummiskey; Karsten Lübke (AStA Wirtschafts und Sozialstatistisches Arch., 2022)

Explaining Artificial Intelligence with Care. - Gero Szepannek; Karsten Lübke (Künstliche Intell., 2022)