A selection gradient describes the relationship between a character trait and a species' relative fitness. A trait may be a physical characteristic, such...

for all r, as otherwise the population would grow indefinitely. The selection gradient is defined as the slope of the invasion exponent at m = r {\displaystyle...

Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate...

In ecology, r/K selection theory relates to the selection of combinations of traits in an organism that trade off between quantity and quality of offspring...

Gradient-index (GRIN) optics is the branch of optics covering optical effects produced by a gradient of the refractive index of a material. Such gradual...

the gradient image is: Compare the edge strength of the current pixel with the edge strength of the pixel in the positive and negative gradient directions...

XGBoost (eXtreme Gradient Boosting) is an open-source software library which provides a regularizing gradient boosting framework for C++, Java, Python...

The two approaches available are gradient-based and gradient-free methods. Gradient-based methods (policy gradient methods) start with a mapping from...

The concept of sexual selection was introduced by Charles Darwin as an element of his theory of natural selection. Sexual selection is a biological way...

wind gradient, more specifically wind speed gradient or wind velocity gradient, or alternatively shear wind, is the vertical component of the gradient of...

In biology, a cline is a measurable gradient in a single characteristic (or biological trait) of a species across its geographical range. Clines usually...

is possible to compute the gradient with respect to hyperparameters and then optimize the hyperparameters using gradient descent. The first usage of...

In the presence of a chemical gradient bacteria will chemotax, or direct their overall motion based on the gradient. If the bacterium senses that it...

data in a pre-specified fashion (e.g., for some mini-batch updates of gradient descent). Reporting: each selected node sends its local model to the server...

Proximal gradient (forward backward splitting) methods for learning is an area of research in optimization and statistical learning theory which studies...

rephasing (selection) or dephasing (elimination) of a particular magnetization transfer pathway. It includes the application of magnetic field gradient pulses...

imaging gradients. If, within one TR, either one of the gradient moments of magnetic gradients along three logical directions, including slice selection direction...

(alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criteria, from some set of available...

localized interactions along environmental gradients can facilitate speciation through frequency-dependent selection and result in patterns of geographical...

involves four steps: coordinate skewing, simplicial subdivision, gradient selection, and kernel summation. An input coordinate is transformed using the...

Sex selection is the attempt to control the sex of the offspring to achieve a desired sex. It can be accomplished in several ways, both pre- and post-implantation...

Fecundity selection, also known as fertility selection, is the fitness advantage resulting from selection on traits that increases the number of offspring...

genetic differentiation for phenotypic traits, and differences in selection gradients across habitats. Such experiments are generally more difficult than...

stage in target selection is specification of target region, a process known as axon pathfinding. Growing neurites follow gradients of cell surface molecules...

correlation, in order to understand the origin of specific electric field gradients in crystals. Despite recent improvements, there are still difficulties...

merge or join, and a revamped gradient tool allowing for more in-depth color manipulation as well as transparency in gradients. CS5 was released in April...

Hyperparameter optimization Stochastic gradient descent Variable metric methods Overfitting Backpropagation AutoML Model selection Self-tuning Murphy, Kevin P....

shrinkage and selection operator; also Lasso, LASSO or L1 regularization) is a regression analysis method that performs both variable selection and regularization...

magnetic Lorentz force from B0 on the current flowing in the gradient coils, the gradient coils will try to move producing loud knocking sounds, for which...

Some of the concepts and tools he introduced, such as the phenotypic selection gradient (univariate or multivariate, directional or quadratic) and the G matrix...