Showing 2025Show all
3 papers · 1 filter
cs.LG2025
Towards Understanding Layer Contributions in Tabular In-Context Learning Models
Amir Rezaei Balef, Mykhailo Koshil, Katharina Eggensperger
Despite the architectural similarities between tabular in-context learning (ICL) models and large language models (LLMs), little is known about how individual layers contribute to…
cs.LG2025
In-Context Decision Making for Optimizing Complex AutoML Pipelines
Amir Rezaei Balef, Katharina Eggensperger
Combined Algorithm Selection and Hyperparameter Optimization (CASH) has been fundamental to traditional AutoML systems. However, with the advancements of pre-trained models, modern…
cs.LG2025
Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning
Amir Rezaei Balef, Claire Vernade, Katharina Eggensperger
The Combined Algorithm Selection and Hyperparameter optimization (CASH) is a challenging resource allocation problem in the field of AutoML. We propose MaxUCB, a max k-armed bandit…