Gradient descent - Gradient descent is an iterative method for minimizing a differentiable function.
Gradient domain - The gradient domain is a way of working with an image through its local changes in value rather than directly through its absolute pixel values.
Gradient reversal - Gradient reversal is an image-processing artifact in which a local brightness change reverses direction after processing: a region that originally became...
Gradient step - A gradient step is one update of a variable using the gradient of an objective.
Gradient temporal-difference learning - Gradient temporal-difference learning refers to methods that estimate value functions by following gradients of carefully defined temporal-difference...
Graduated optimization - Graduated optimization tackles a difficult objective through a sequence of simpler approximations.
Grafting (decision trees) - Grafting is a decision-tree learning technique that adds branches to an already constructed tree to improve its classifications.
Gram matrix - A Gram matrix records the pairwise inner products of a set of vectors.
Grammar - A grammar is a formal description of how valid expressions can be structured in a language.
Grammar-based code - A grammar-based code represents data using a formal grammar that reconstructs the original sequence through reusable rules.
Grammar induction - Grammar induction is the process of learning a grammatical representation or structural regularities from examples.
Grammar systems theory - Grammar systems theory studies collections of formal grammars that cooperate or communicate to generate formal languages.
Grammatical function - Grammatical function is the syntactic role an expression has within a larger construction, such as subject, object, complement, or modifier.
Grammatical relation - A grammatical relation is a syntactic relationship between an expression and another part of a sentence, such as the relationship of a subject or object to...
Granger causality - Granger causality is a predictive relationship between time series: the past of one series helps predict another beyond the information already included in...
Granular computing - Granular computing is an approach to representing and solving problems using meaningful groups or units of information called granules.
Graph - A graph is a mathematical structure made of vertices, also called nodes, and edges that represent relationships between them.
Graph clustering - Graph clustering groups data points represented as nodes of a graph using the relationships encoded by its edges.
Graph Coarsening Algorithm - A graph coarsening algorithm creates a smaller graph by combining selected vertices into groups and aggregating their connections.
Graph coloring - Graph coloring assigns labels, traditionally called colors, to graph elements under specified compatibility rules.
Graph Convolutional Network - A Graph Convolutional Network, or GCN, is a neural-network architecture that learns representations using a graph's connections together with features...
Graph Convolutional Policy Network - Graph Convolutional Policy Network, or GCPN, is a model introduced for goal-directed graph generation using reinforcement learning.
Graph cut optimization - Graph cut optimization solves certain labeling problems by constructing a weighted graph whose cuts correspond to candidate solutions.
Graph-cut segmentation - Graph-cut segmentation divides an image into labeled regions by constructing a weighted graph and finding a cut that minimizes a defined cost.
Graph entropy - In the information-theoretic sense associated with Körner, graph entropy measures a graph together with a probability distribution over its vertices.
Graph Hashing - Graph hashing converts a graph's selected structural and attribute information into a compact identifier.
Graph isomorphism - Graph isomorphism is a one-to-one correspondence between the vertices of two graphs that preserves their connections.
Graph kernel - A graph kernel is a function that compares two graphs in a way suitable for kernel-based learning, typically corresponding to an inner product between their...
Graph Language Model - A Graph Language Model combines language representations with information about graph structure, such as entities and their relationships.
Graph matching - Graph matching seeks a correspondence between vertices, edges or substructures of two graphs so that their attributes and relationships agree as well as the...
Graph neural network - A graph neural network, or GNN, is a neural model designed to learn from data represented as a graph of nodes and edges.
Graph of a function - The graph of a function is the set of all input-output pairs produced by that function over its specified domain.
Graph partitioning - Graph partitioning divides a graph's vertices into groups according to a defined objective and constraints.
Graph representation - A graph representation describes entities as vertices and relationships as edges, together with any relevant attributes.
Graph search - Graph search is a family of problem-solving procedures that explore states and transitions while accounting for states reached more than once.
Graph semantics - Graph semantics is the meaning carried by the structure of a graph: what the nodes represent, what the edges assert and how relationships between things...
Graphical data editing - Graphical data editing is the use of graphs to identify potentially erroneous, inconsistent, or otherwise unusual data for investigation and possible...
Graphical degree sequence - A graphical degree sequence is a list of nonnegative integers that can be realized as the node degrees of a graph of the specified kind.
Graphical lasso - Graphical lasso is a statistical method for estimating a sparse inverse covariance matrix using an L1 penalty.
Graphical time warping - Graphical time warping is a framework for jointly aligning multiple pairs of time series while modeling relationships among their alignment paths.
Graphite graph generative model - Graphite is a graph generative modeling framework that combines latent node representations with an iterative graph-neural-network decoder.
Graphplan - Graphplan is an automated planning algorithm developed by Avrim Blum and Merrick Furst.
Grasping - Grasping is the process of establishing and maintaining physical contact that lets a robot hold or control an object.
Gray scale - Gray scale, commonly written grayscale, represents an image using a single intensity-related value at each pixel rather than separate color components.
Grey Wolf Optimization - Grey Wolf Optimization is a population-based numerical search method inspired by an abstract model of gray-wolf social roles and hunting.
Gray-world assumption - The gray-world assumption is the idea that the average surface color across a sufficiently varied scene is approximately neutral.
Great deluge algorithm - The Great deluge algorithm is a local-search optimization heuristic that accepts candidate solutions according to a changing quality threshold.
Greedy agent - A greedy agent is an agent that, at each decision, picks the action that looks best right now according to its immediate measure, without searching ahead...