Variational approximation - A variational approximation replaces a difficult target distribution with a manageable distribution selected by optimization.
Variational autoencoder - A variational autoencoder, or VAE, is a probabilistic generative model that learns a latent-variable representation of data together with an approximate...
Variational Bayes expectation maximization - Variational Bayes expectation maximization, often called variational Bayesian EM or VBEM, is an iterative approach to approximate Bayesian inference that...
Variational Bayesian methods - Variational Bayesian methods approximate a Bayesian posterior by choosing a tractable probability distribution from a specified family and optimizing it to...
Variational bound integration - Variational bound integration approximates a difficult integral by replacing its integrand with a tractable lower bound and integrating that bound.
Variational bound optimization - Variational bound optimization improves a difficult objective by working with a more tractable bound on it.
Variational expectation maximization - Variational expectation maximization, or variational EM, is an alternating optimization method for latent-variable models when exact posterior inference is...
Variational filtering sequential Monte Carlo - Variational filtering sequential Monte Carlo refers here to combining particle-based sequential inference with variational optimization of proposals or...
Variational lower bound - A variational lower bound is an expression, controlled by adjustable auxiliary choices, that does not exceed a target quantity.
Variational message passing - Variational message passing, or VMP, is a way to organize variational inference as local computations and messages in a probabilistic graphical model.
Variational parameters - Variational parameters are adjustable quantities that specify an approximate distribution used in variational inference.
Variational posterior - A variational posterior is a distribution fitted through variational inference to approximate a model's posterior distribution after observing data.
Variational recurrent neural network - A variational recurrent neural network, or VRNN, is a sequence model that combines recurrent neural-network memory with latent random variables at each time...
Vauquois triangle - Definition: The Vauquois triangle is a conceptual diagram of machine-translation approaches.
VC dimension - VC dimension, short for Vapnik - Chervonenkis dimension, measures the expressive capacity of a class of binary classifiers.
Vecchia approximation - The Vecchia approximation is a way to approximate a large joint probability distribution, especially a Gaussian process, by multiplying conditional...
Vector - A vector is an element of a vector space.
Vector Autoregression - Vector autoregression, or VAR, is a statistical time-series model that predicts several variables together using their own past values and the past values...
Vector Database - A vector database stores and retrieves data using numerical vectors, with facilities designed for similarity search and management of the associated records.
Vector-field consistency - Vector-field consistency, or VFC, is a research consistency model for replicated data that varies permitted replica divergence according to locality.
Vector field histograms - Vector field histograms are directional representations used in a mobile-robot obstacle-avoidance method known as VFH.
Vector field reconstruction - Vector field reconstruction estimates a function that assigns a vector to each location in a domain, using incomplete, noisy, or scattered observations.
Vector-Jacobian product - A vector-Jacobian product, or VJP, combines sensitivities at a function's outputs with its derivatives to produce sensitivities at its inputs.
Vector length - Vector length measures the magnitude of a vector according to a chosen norm.
Vector optimization - Vector optimization optimizes an objective whose value is a vector rather than a single number, using a specified rule for comparing vectors.
Vector quantization - Vector quantization represents an input vector by one of a finite set of representative vectors called a codebook.
Vector-quantized generative adversarial network - A vector-quantized generative adversarial network, usually called VQGAN, learns a discrete codebook for image representations while using reconstruction...
Vector-quantized variational autoencoder - A vector-quantized variational autoencoder, or VQ-VAE, is a generative representation model that maps encoder outputs to entries in a learned discrete...
Vector semantics - Vector semantics studies and represents aspects of meaning using vectors and relationships between them.
Vehicle interface layer - A vehicle interface layer is the software boundary that translates between a vehicle's hardware-specific messages and the more general commands and status...
Velar sound - Definition: A velar sound is a speech sound whose primary constriction involves the back of the tongue and the velum, or soft palate.
Venn diagrams - Venn diagrams use overlapping regions to represent sets and the possible combinations of membership among them.
Verb - Definition: A verb is a grammatical class of word that commonly expresses an action, event, process or state and helps organize a clause.
Verb alternations - Definition: Verb alternations are related ways in which a verb's participants can be expressed in sentence structure.
Verb phrase - Definition: A verb phrase is a grammatical constituent organized around a verb.
Verifiable computing - Verifiable computing enables a client to delegate a computation and check evidence that the returned result matches the specified computation on the...
Verification - Verification is the process of checking whether a system satisfies specified requirements.
Verification and validation - Verification and validation, often abbreviated V&V, are complementary activities for assessing a system.
Version space - A version space is the set of hypotheses within a chosen hypothesis space that are consistent with all the training examples observed so far.
Version space learning - Version space learning represents all hypotheses in a chosen hypothesis class that agree with the training examples seen so far.
Vertical federated learning - Vertical federated learning is collaborative model training in which participants hold different features about the same or overlapping entities.
Very large database - A very large database, or VLDB, is a database whose scale creates significant challenges for processing, administration and maintenance.
Very large-scale neighborhood search - Very large-scale neighborhood search is an optimization approach that seeks improvements within a very large set of related candidate solutions, often of...
Very long instruction word - Very long instruction word, or VLIW, describes a processor architecture that exposes parallel execution opportunities to software through instructions or...
VF2++ - VF2++ is an algorithm for testing graph isomorphism: whether two graphs have the same structure after consistently renaming their vertices.
Vibe coding - Vibe coding is an informal term for creating software by describing desired behavior to a generative AI system and iterating on what it produces.
Vibrance - Vibrance is an image-editing control that adjusts color intensity selectively rather than applying one uniform saturation change everywhere.
Vickrey-Clarke-Groves - Vickrey - Clarke - Groves, usually abbreviated VCG, is a mechanism-design approach that selects an outcome maximizing the sum of reported values and uses...