1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ML2025
Optimizing Kernel Discrepancies via Subset Selection
Deyao Chen, François Clément, Carola Doerr +1
Kernel discrepancies are a powerful tool for analyzing worst-case errors in quasi-Monte Carlo (QMC) methods. Building on recent advances in optimizing such discrepancy measures, we…
cs.LG2025
carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks
Carolin Benjamins, Helena Graf, Sarah Segel +14
Hyperparameter Optimization (HPO) is crucial to develop well-performing machine learning models. In order to ease prototyping and benchmarking of HPO methods, we propose carps, a b…
cs.LG2023★ 1 cited
Using Automated Algorithm Configuration for Parameter Control
Deyao Chen, Maxim Buzdalov, Carola Doerr +1
Dynamic Algorithm Configuration (DAC) tackles the question of how to automatically learn policies to control parameters of algorithms in a data-driven fashion. This question has re…