Delete list - A delete list is the set of facts that an action makes false in a STRIPS-style planning model.
Deletion Anomaly - A deletion anomaly occurs when deleting a row to remove one fact unintentionally removes another independent fact that should remain represented in the...
Deliberative layer - A deliberative layer is the part of an agent or robot architecture that performs planning, reasoning, or other computations requiring more time than...
Delphi method - The Delphi method is a structured process for collecting and refining judgments from a panel through repeated rounds of questions and controlled feedback.
Delta encoding - Delta encoding represents information through differences from a known reference instead of repeating the whole value or object.
Delta feature - A delta feature is an input built from the change between values, such as this month's sales minus last month's, so the model sees movement rather than only...
Delta modulation - Delta modulation is a signal-coding technique that represents a changing signal through a sequence of small upward or downward adjustments.
Delta rule - The delta rule is an error-driven learning rule that adjusts a model's weights in the direction that reduces a squared-error objective.
Deming regression - Deming regression estimates a straight-line relationship when both measured variables contain error.
Demographic parity - Demographic parity is a statistical fairness criterion requiring a model's predictions to be independent of a specified sensitive attribute.
Demonic nondeterminism - Demonic nondeterminism is an interpretation of unspecified choice in which a required guarantee must withstand every permitted alternative, including...
Demosaicking - Demosaicking reconstructs full-color image values from measurements captured through a color filter array.
Dempster-Shafer theory - Dempster-Shafer theory, also called evidence theory or the theory of belief functions, is a mathematical framework for representing uncertain evidence.
Denial-of-service - Denial-of-service, commonly abbreviated DoS, is the prevention of authorized access to a resource or a delay that makes required operations unavailable when...
Denoising - Denoising is removing unwanted noise from data, such as static from audio, grain from images or jitter from measurements, so the underlying signal is easier...
Denoising Auto Encoder - A denoising autoencoder is a neural network trained to reconstruct an original input from a deliberately corrupted version.
Denoising diffusion probabilistic model - A denoising diffusion probabilistic model, or DDPM, generates data through a learned sequence of denoising transitions.
Denoising score matching - Denoising score matching trains a model to estimate the gradient of a noisy data distribution's log density by using clean examples and deliberately...
Dense feature - A dense feature is an input whose value is almost always present and meaningful, such as age or order total, as opposed to a sparse feature that is empty or...
Density-based clustering validation - Density-Based Clustering Validation, or DBCV, is a score for assessing clustering solutions using density-based ideas of connection within groups and...
Density estimation - Density estimation uses observed data to estimate a probability density describing how values are distributed.
Density kernel - A density kernel is a weighting function used to spread an observation's contribution over nearby locations when estimating a probability density.
Dental sound - A dental sound is a speech sound whose principal constriction involves the tongue at the teeth.
Dependability - Dependability is the ability of a system to provide a service that people have sound reasons to rely on.
Dependability state model - A dependability state model represents a system through states such as operational, degraded and failed, together with possible transitions between them.
Dependency-directed backtracking - Dependency-directed backtracking is a search and reasoning approach that uses the dependencies behind a failure to decide which earlier assumptions or...
Dependency grammar - Dependency grammar is an approach to describing sentence structure through relationships between words, typically linking a head word to its dependents.
Dependency network (graphical model) - A dependency network is a probabilistic graphical model that describes each variable through a conditional distribution given selected other variables.
Dependency tree - A dependency tree represents the syntactic structure of a sentence through directed relations between its words.
Dependent Dirichlet process - A dependent Dirichlet process is a Bayesian construction for a collection of related random probability distributions indexed by predictors, groups, time...
Dependent variable - A dependent variable is the outcome or response a statistical analysis seeks to explain, compare, or predict.
Deployment - Deployment is the process of placing an AI system or component into its intended operating environment and making it available for use.
Deployment Bias - Deployment bias arises when the way an AI system is actually used differs from the role or context for which it was designed and evaluated, creating...
Depth - Depth is how many layers or levels a model has, counting from input to output, and more depth lets a model build more complicated ideas from simpler ones.
Depth First Search - Depth First Search, usually abbreviated DFS, is a graph or tree traversal strategy that explores one branch as far as it can before returning to explore...
Depth First Search on Edges - Depth First Search on Edges is a traversal that explores graph connections in depth-first order while tracking edges as the items to visit.
Depth image - A depth image is an image-shaped array whose values describe the depth of visible scene surfaces rather than their ordinary color or brightness.
Depth map - A depth map associates image locations with estimates or measurements of scene depth.
Depthwise separable convolutional neural network - A depthwise separable convolutional neural network is a convolutional network that uses depthwise separable convolutions as important building blocks.
Deriche edge detector - The Deriche edge detector is a classical image-edge method based on recursively implemented filters derived from edge-detection criteria related to Canny's...
Derivational morphemes - Derivational morphemes are meaningful word-building units that help form new lexical words from a base. They can change meaning, grammatical category or both.
Derivative-free optimization - Derivative-free optimization searches for good decision-variable values without requiring derivatives of the objective or constraints to be supplied.
Derived Relation - A derived relation is a relation obtained by applying an expression or query to other relations rather than treating its contents as independently supplied...
Description logic - Description logic is a family of formal knowledge-representation languages for describing classes of things, their relationships and individual instances.
Descriptive analytics - Descriptive analytics summarizes recorded data to show what has happened or what is currently observed.