Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the ...

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...

At the IGFAE, where he has already completed his doctoral thesis, he will develop his line of research in non-linear evolution equations ... as a first approximation, by considering the cat ...

For homogeneous linear first-order differential equations, it is shown that Picard’s method of successive approximations is effective to furnish a closed-form solution even if the coefficient is an ...

This book presents an approximation theory for a general class of nonlinear evolution equations in Banach spaces and the semigroup theory, including the linear (Hille–Yosida), nonlinear ...

Based on the proposed two approaches, a set of approximations to damped Burger’s equation are derived ... or perturbation, can solve both linear and nonlinear PDEs. The determination of the ...

The low learning curve only assumes prior knowledge of ordinary differential equations and basic concepts of statistic, together with understanding of linear algebra ... 9.6 (Linearization and ...

Two classical equations of motion for SBs are derived in the presence of a linear and a trigonometric decrease for ... The angular distance, adopting the minimax approximation, is derived for three ...

Abstract: Nonlinear feedback design via state-dependent Riccati equations is well established but unfeasible for large-scale systems because of computational costs. If the system can be embedded in ...