RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization. - Helena Kotthaus; Jakob Richter; Andreas Lang 002; Janek Thomas; Bernd Bischl; Peter Marwedel; Jörg Rahnenführer; Michel Lang (LION, 2017)

Can Flexible Multi-Core Scheduling Help to Execute Machine Learning Algorithms Resource-Efficiently? - Helena Kotthaus; Lea Schönberger; Andreas Lang 002; Jian-Jia Chen; Peter Marwedel (SCOPES, 2019)

BETULA: Numerically Stable CF-Trees for BIRCH Clustering. - Andreas Lang 002; Erich Schubert (SISAP, 2020)

Accelerating Spherical k-Means. - Erich Schubert; Andreas Lang 002; Gloria Feher (SISAP, 2021)

Data Aggregation for Hierarchical Clustering. - Erich Schubert; Andreas Lang 002 (Mach. Learn. under Resour. Constraints Vol. 1 (1), 2022)

BETULA: Fast clustering of large data with improved BIRCH CF-Trees. - Andreas Lang 002; Erich Schubert (Inf. Syst., 2022)

Accelerating k-Means Clustering with Cover Trees. - Andreas Lang 002; Erich Schubert (SISAP, 2023)

Data Aggregation for Hierarchical Clustering. - Erich Schubert; Andreas Lang 002 (CoRR, 2023)

Advancing the PAM Algorithm to Semi-supervised k-Medoids Clustering. - Miriama Jánosová; Andreas Lang 002; Petra Budíková; Erich Schubert; Vlastislav Dohnal (SISAP, 2024)