Search Results for author:
Found 3 papers, 1 papers with code
Instance-wise algorithm configuration with graph neural networks
We pose this task as a supervised learning problem: First, we compile a large dataset of the solver performance for various configurations and all provided MILP instances.
A Holistic Assessment of the Reliability of Machine Learning Systems
As machine learning (ML) systems increasingly permeate high-stakes settings such as healthcare, transportation, military, and national security, concerns regarding their reliability have emerged.
Towards a Framework for Deep Learning Certification in Safety-Critical Applications Using Inherently Safe Design and Run-Time Error Detection
Although an ever-growing number of applications employ deep learning based systems for prediction, decision-making, or state estimation, almost no certification processes have been established that would allow such systems to be deployed in safety-critical applications.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
