LongCat-Flash employs a mixture of experts (MoE) architecture with 560 billion parameters, which enhances model capabilities ...

Hyperparameter optimization is an important issue in convolutional neural networks (CNNs), which is an appropriate deep learning network for image classification. Several classical and metaheuristic ...

This research investigates the optimization of Convolutional and Dense Neural Networks (CNNs and DNNs) for autonomous steering using the (N + M) Evolution Strategy (ES) with the 1/5th success rule.

We therefore relied on Bayesian optimization over a defined hyperparameter space, using cross-validated classification loss as the objective. This is a standard and appropriate method for tuning ...