1 citations · 2 across the 8 of their papers we have counts for
3 papers · 1 filter
Provably Reduced Sample Cost in Prior-Guided Hyperparameter Optimization
Leona Hennig, Jasmin Brandt, Lukas Fehring +3
Large-scale hyperparameter optimization (HPO) in automated machine learning (AutoML) consumes substantial computational resources, raising growing concerns about scalability and en…
No learning rates needed: Introducing SALSA -- Stable Armijo Line Search Adaptation
Philip Kenneweg, Tristan Kenneweg, Fabian Fumagalli +1
In recent studies, line search methods have been demonstrated to significantly enhance the performance of conventional stochastic gradient descent techniques across various dataset…
Improving Line Search Methods for Large Scale Neural Network Training
Philip Kenneweg, Tristan Kenneweg, Barbara Hammer
In recent studies, line search methods have shown significant improvements in the performance of traditional stochastic gradient descent techniques, eliminating the need for a spec…