Optimization is one of the factors in machine learning to help model training during backpropagation. This conducted by adjusting weights minimize loss function and overcome dimensional problems. Also, gradient descent method a simple approach backpropagation solve minimum The mini-batch (MBGD) methods proven be powerful for large-scale learning. addition several approaches MBGD such as AB, BN,...

Gradient boosted trees (GBTs) are ubiquitous models used by researchers, machine learning (ML) practitioners, and data scientists because of their robust performance, interpretable behavior, ease-of-use. One critical challenge in training GBTs is the tuning hyperparameters. In practice, selecting these hyperparameters often done manually. Recently, ML community has advocated for through black-b...

In this work, an approach for the development of adaptive fuzzy models is presented. The approach allows to incorporate the system dynamics into the fuzzy membership functions which are defined in terms of a dynamic function with adjustable parameters. These parameters are adapted using a gradient descent based algorithm. Some application examples to illustrate the performance of the dynamical ...