Since deep neural networks were developed, they have made huge contributions to
everyday lives. Machine learning provides more rational advice than humans are capable of …

For any machine learning model, finding the optimal hyperparameter setting has a direct
and significant impact on the model's performance. In this paper, we discuss different types …

In a broad range of computer vision tasks, convolutional neural networks (CNNs) are one of
the most prominent techniques due to their outstanding performance. Yet it is not trivial to …

Workers healthcare gained a lot of attention recently as many countries are increasingly
concerning about welfare. This paper faces the problem of predicting occupational disease …

It is already reported in the literature that the performance of a machine learning algorithm is
greatly impacted by performing proper Hyper-Parameter optimization. One of the ways to …

Weather forecasting plays a vital role in numerous sectors, but accurately capturing the
complex dynamics of weather systems remains a challenge for traditional statistical models …

Deep neural networks have accomplished enormous progress in tackling many problems.
More specifically, convolutional neural network (CNN) is a category of deep networks that …

Graph representation of structured data can facilitate the extraction of stereoscopic features,
and it has demonstrated excellent ability when working with deep learning systems, the so …

In Artificial Intelligence, there is an increasing demand for adaptive models capable of
dealing with a diverse spectrum of learning tasks, surpassing the limitations of systems …

The performance of a simulation-optimization algorithm, aka a solver, depends on its
parameter settings. Much of the research to date has focused on how a solver's parameters …