Abstract: Real-world software–hardware co-design for AI accelerators must meet strict constraints on accuracy and PPA, making design space exploration both costly and inefficient. In this work, we ...

Abstract: This paper presents a comparative study of LLM-guided parameter tuning and Bayesian Optimization (BO) for automated PI parameter adjustment in Low Level Radio Frequency (LLRF) systems. Both ...

In this paper we develop a dynamic form of Bayesian optimization for machine learning models with the goal of rapidly finding good hyperparameter settings. Our method uses the partial information ...

Learn how Kaggle works and how to make the most of competitions from two expert Kaggle Grandmasters Sharpen your modeling skills with ensembling, feature engineering, adversarial validation, AutoML, ...