Search Results for author:
Found 3 papers, 1 papers with code
Differentially Evolving Memory Ensembles: Pareto Optimization based on Computational Intelligence for Embedded Memories on a System Level
As the relative power, performance, and area (PPA) impact of embedded memories continues to grow, proper parameterization of each of the thousands of memories on a chip is essential.
Predicting Memory Compiler Performance Outputs using Feed-Forward Neural Networks
A key task in the design flow of a chip is to find optimal memory compiler parametrizations which on the one hand fulfill system requirements while on the other hand optimize PPA.
Oversampling for Imbalanced Learning Based on K-Means and SMOTE
Learning from class-imbalanced data continues to be a common and challenging problem in supervised learning as standard classification algorithms are designed to handle balanced class distributions.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
