Davis-Putnam algorithm - The Davis - Putnam algorithm is a resolution-based procedure for deciding satisfiability of propositional formulas in conjunctive normal form.
DDPM objective - The DDPM objective is a training criterion for a denoising diffusion probabilistic model.
De Boor's algorithm - De Boor's algorithm evaluates a B-spline curve at a specified parameter value through repeated weighted combinations of nearby control points.
De Casteljau's algorithm - De Casteljau's algorithm evaluates a Bézier curve by repeatedly interpolating between neighboring control points.
De Finetti's theorem - De Finetti's theorem connects exchangeability with conditional independence.
De-identification - De-identification is the process of reducing the association between data and the people or other subjects it describes.
De Moivre's law - De Moivre's law is a simple actuarial survival model in which lifetime is uniformly distributed between zero and a specified limiting age.
De-perimeterization - De-perimeterization is the shift away from treating an organization's outer network boundary as the main basis for protecting its information.
De-skilling - De-skilling is the reduction or loss of a person's ability to perform a task, or the redesign of work so that less expertise is required or exercised.
Deadlock prevention algorithms - Deadlock prevention algorithms are rules that stop a group of concurrent tasks from entering a circular wait in which none can proceed.
Deadly triad in reinforcement learning - The deadly triad in reinforcement learning is the combination of function approximation, bootstrapping, and off-policy learning.
Debevec - Malik calibration - Debevec - Malik calibration estimates an imaging system's response curve from photographs of the same static scene taken at known exposure durations.
Debiasing - Debiasing is the process of identifying and reducing a specified unwanted bias in data, representations, models, or their use.
Decayed MCMC - Decayed MCMC is an approximate filtering method that uses Markov chain Monte Carlo over possible state histories while updating recent states more...
Decentralized application - A decentralized application, often shortened to dapp, is an application whose important operations run through a decentralized network rather than depending...
Decentralized autonomous organization - A decentralized autonomous organization, or DAO, is a group that coordinates decisions and shared resources using collectively defined governance...
Decentralized computing - Decentralized computing is an approach in which computing functions and some control over them are spread across multiple participants or nodes instead of...
Decentralized planning - Decentralized planning develops coordinated behavior for multiple agents that make decisions using their own available information and authority.
Decile - A decile is a quantile associated with dividing an ordered distribution into ten parts.
Decision analysis - Decision analysis is a structured approach to choosing among alternatives by making objectives, uncertainties, consequences and preferences explicit.
Decision boundary - A decision boundary is the dividing line, or surface, in the space of inputs where a classifier switches from predicting one class to another, such as the...
Decision forest - A decision forest is a model made of many decision trees whose answers are combined, usually by voting or averaging, so the group predicts better than any...
Decision lists - A decision list is an ordered sequence of rules in which the first matching condition determines the output.
Decision network - A decision network is a graphical model that combines uncertain variables, available decisions and utilities to support choosing actions under uncertainty.
Decision nodes - Decision nodes represent choices that an agent or decision maker can control in a decision model.
Decision region - A decision region is the set of inputs that a classifier assigns to a particular output label.
Decision support system - A decision support system, or DSS, is a computer-based system that helps people make decisions by organizing relevant information, analyzing alternatives...
Decision-theoretic metareasoning - Decision-theoretic metareasoning uses decision theory to choose which computations to perform, how much effort to spend and when to stop thinking and act.
Decision theory - Decision theory studies how choices relate to beliefs, uncertainty and preferences.
Decision tree - A decision tree is a model that predicts an answer through a sequence of yes-or-no style questions about the input, arranged like the branches of a tree...
Decision tree pruning - Decision tree pruning is the practice of cutting branches off a grown decision tree so it stops memorizing the training data's noise and predicts new cases...
Deck imputation - Deck imputation fills a missing data item using information from a donor record.
Decoder - A decoder is the part of a model that turns an internal numeric representation back into an output people can use, such as words, images or predictions.
Decoder models - Decoder models, in the language-modeling sense used here, generate sequences by predicting the next token from preceding context.
Decoder-only model - A decoder-only model is a neural sequence model built around a decoder stack without a separate encoder stack for the text input.
Decoding - Decoding is the inference process that turns a model's scores or probabilities into a selected output sequence.
Decomposition - Decomposition is the process of expressing a problem or structure as smaller parts whose solutions or properties can be combined to address the original whole.
Decomposition Algorithm - A decomposition algorithm is a systematic procedure for dividing a relation schema into smaller relation schemas to satisfy a chosen database normal form.
Decomposition of time series - Decomposition of time series separates observations recorded over time into components representing different patterns.
Deconvolutional Network - A deconvolutional network, in the historical sense used by the supplied ontology, is an unsupervised model that learns hierarchical image representations by...
Deduction theorem - The deduction theorem connects reasoning from an assumption with reasoning about an implication.
Deductive classifier - A deductive classifier is a reasoning system that determines classifications from formally stated knowledge and logical consequences.
Deductive databases - Deductive databases combine stored facts with logical rules that derive additional information when answering queries.
Deductive imputation - Deductive imputation supplies a missing value by applying logical relationships to information already available.
Deductive language - A deductive language is a language for expressing facts, relationships and logical rules so that a system can derive conclusions from them.
Deductive learning - Deductive learning is learning that uses existing knowledge and logical reasoning to derive reusable knowledge or procedures.
Deductive synthesis - Deductive synthesis is the construction of a program from a specification by applying logical reasoning and justified transformation rules.