ABSTRACT: The canonical affinity-threshold model of thymic T-cell selection posits that thymocyte fate is determined by TCR-pMHC integrated affinity. However, this model fails to explain high ...

Abstract: Hyperparameter tuning is a crucial step in the development of machine learning models, as it directly impacts their performance and generalization ability. Traditional methods for ...

Hyperparameter tuning is critical to the success of cross-device federated learning applications. Unfortunately, federated networks face issues of scale, heterogeneity, and privacy; addressing these ...

Abstract: For distributed-drive electric vehicles, torque vectoring control based on model predictive control (MPC) has emerged as a preferred strategy to achieve superior performance across diverse ...

A modular and production-ready toolkit for evaluating machine learning models using accuracy, precision, recall, F1-score, and cross-validation. Includes advanced hyperparameter tuning (GridSearchCV, ...

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.