8 citations · 14 across the 4 of their papers we have counts for
4 papers · 1 filter
Dynamic Hyperparameter Importance for Efficient Multi-Objective Optimization
Daphne Theodorakopoulos, Marcel Wever, Marius Lindauer
Choosing a suitable ML model is a complex task that can depend on several objectives, e.g., accuracy, fairness, or energy consumption. In practice, this requires trading off multip…
FITS: Towards an AI-Driven Fashion Information Tool for Sustainability
Daphne Theodorakopoulos, Elisabeth Eberling, Miriam Bodenheimer +2
Access to credible sustainability information in the fashion industry remains limited and challenging to interpret, despite growing public and regulatory demands for transparency.…
Hyperparameter Importance Analysis for Multi-Objective AutoML
Daphne Theodorakopoulos, Frederic Stahl, Marius Lindauer
Hyperparameter optimization plays a pivotal role in enhancing the predictive performance and generalization capabilities of ML models. However, in many applications, we do not only…
AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks
Alexander Tornede, Difan Deng, Theresa Eimer +8
The fields of both Natural Language Processing (NLP) and Automated Machine Learning (AutoML) have achieved remarkable results over the past years. In NLP, especially Large Language…