In vector calculus, the gradient of a scalar-valued differentiable function f {\displaystyle f} of several variables is the vector field (or vector-valued...

Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for finding a local minimum of a differentiable...

Gradient boosting is a machine learning technique based on boosting in a functional space, where the target is pseudo-residuals rather than the typical...

In machine learning, the vanishing gradient problem is encountered when training neural networks with gradient-based learning methods and backpropagation...

Stochastic gradient descent (often abbreviated SGD) is an iterative method for optimizing an objective function with suitable smoothness properties (e...

Geothermal gradient is the rate of change in temperature with respect to increasing depth in Earth's interior. As a general rule, the crust temperature...

surface gradient is a vector differential operator that is similar to the conventional gradient. The distinction is that the surface gradient takes effect...

rate. Gradient may also refer to: Gradient sro, a Czech aircraft manufacturer Image gradient, a gradual change or blending of color Color gradient, a range...

The gradient theorem, also known as the fundamental theorem of calculus for line integrals, says that a line integral through a gradient field can be evaluated...

A temperature gradient is a physical quantity that describes in which direction and at what rate the temperature changes the most rapidly around a particular...