no code implementations • 29 Dec 2023 • Joshua Inman, Tanmay Khandait, Giulia Pedrielli, Lalitha Sankar
The performance of modern machine learning algorithms depends upon the selection of a set of hyperparameters.
no code implementations • 16 May 2022 • Haowei Wang, Ercong Zhang, Szu Hui Ng, Giulia Pedrielli
In this study, we propose a model aggregation method in the Bayesian optimization (MamBO) algorithm for efficiently solving high-dimensional large-scale optimization problems.
no code implementations • 8 May 2022 • Wei Xie, Giulia Pedrielli
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.
no code implementations • 20 Oct 2021 • Giulia Pedrielli, Tanmay Kandhait, Surdeep Chotaliya, Quinn Thibeault, Hao Huang, Mauricio Castillo-Effen, Georgios Fainekos
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.