Search Results for author:
Found 4 papers, 0 papers with code
Parameter Optimization with Conscious Allocation (POCA)
The performance of modern machine learning algorithms depends upon the selection of a set of hyperparameters.
A model aggregation approach for high-dimensional large-scale optimization
In this study, we propose a model aggregation method in the Bayesian optimization (MamBO) algorithm for efficiently solving high-dimensional large-scale optimization problems.
From Discovery to Production: Challenges and Novel Methodologies for Next Generation Biomanufacturing
The increasingly pressing demand of novel drugs (e. g., gene therapies for personalized cancer care, ever evolving vaccines) with unprecedented levels of personalization, has put a remarkable pressure on the traditionally long time required by the pharma R&D and manufacturing to go from design to production of new products.
Part-X: A Family of Stochastic Algorithms for Search-Based Test Generation with Probabilistic Guarantees
Requirements driven search-based testing (also known as falsification) has proven to be a practical and effective method for discovering erroneous behaviors in Cyber-Physical Systems.
