3 papers
cs.NE2026
Evolutionary Mapping of Neural Networks to Spatial Accelerators
Alessandro Pierro, Jonathan Timcheck, Jason Yik +3
Spatial accelerators, composed of arrays of compute-memory integrated units, offer an attractive platform for deploying inference workloads with low latency and low energy consumpt…
cs.LG2025
DeepCAVE: A Visualization and Analysis Tool for Automated Machine Learning
Sarah Segel, Helena Graf, Edward Bergman +5
Hyperparameter optimization (HPO), as a central paradigm of AutoML, is crucial for leveraging the full potential of machine learning (ML) models; yet its complexity poses challenge…
cs.LG2025
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization
Marcel Wever, Maximilian Muschalik, Fabian Fumagalli +1
Hyperparameter optimization (HPO) is a crucial step in achieving strong predictive performance. Yet, the impact of individual hyperparameters on model generalization is highly cont…