Explicit parallelism - Explicit parallelism is a programming approach in which the programmer specifies opportunities or structures for concurrent execution.
Explicit semantic analysis - Explicit semantic analysis, usually abbreviated ESA, represents text as a weighted vector of named concepts drawn from a knowledge collection.
Exploding gradient problem - The exploding gradient problem occurs when gradients become excessively large during model training, making parameter updates unstable or numerically...
Exploitation - Exploitation is choosing an action that looks best according to what an agent currently knows.
Exploration - Exploration in reinforcement learning means taking actions to learn more about their outcomes or the environment, rather than always choosing the action...
Exploration bonus - An exploration bonus is an extra incentive used by a learning algorithm to favor actions or states that are uncertain, unfamiliar, or insufficiently tested.
Exploration function - An exploration function is a rule that combines an agent's current value estimates with information about how well actions or states have been explored.
Exploration problem - The exploration problem is the challenge of deciding how an AI agent should gather experience when it does not yet know which actions lead to useful outcomes.
Exploratory data analysis - Exploratory data analysis, or EDA, is an approach to understanding a dataset through summaries, visualizations, and iterative investigation before...
Exploratory forecasting - Exploratory forecasting examines how the future might develop from present conditions, past trends, and alternative assumptions.
Explore-then-commit algorithm - The explore-then-commit algorithm is a strategy for a stochastic multi-armed bandit problem that separates learning from exploitation.
Exploring starts - Exploring starts is an assumption or sampling arrangement in episodic reinforcement learning under which every relevant state-action pair has a nonzero...
Exponential dispersion family - An exponential dispersion family is a class of probability distributions with a common mathematical form that separates a mean-related parameter from a...
Exponential dispersion model - An exponential dispersion model is a family of probability distributions whose density or probability mass function separates a natural parameter from a...
Exponential family - An exponential family is a class of probability distributions whose probability mass or density can be written in a shared mathematical form: p(x; η) = h(x)...
Exponential family factor analysis - Exponential family factor analysis is a latent-variable approach that explains many observed measurements using fewer hidden factors while allowing...
Exponential Function - An exponential function places the variable in the exponent of a fixed positive base.
Exponential-Golomb coding - Exponential-Golomb coding, often shortened to Exp-Golomb coding, is a family of self-delimiting binary codes for nonnegative integers.
Exponential growth - Exponential growth is growth in which a quantity increases by a constant proportion over equal time intervals.
Exponential-logarithmic distribution - The exponential-logarithmic distribution is a continuous probability distribution for positive lifetimes, formed by combining exponential failure times with...
Exponential search - Exponential search is a method for finding a value in sorted data by first expanding a search boundary geometrically, usually by doubling positions, and...
Exponential smoothing - Exponential smoothing is a family of methods that updates estimates of a time series as new observations arrive.
Exponential Smoothing State Space Model - An exponential smoothing state space model is a statistical time-series model that expresses exponential smoothing through equations for observations and...
Exposure bracketing - Exposure bracketing is the capture of several images of the same scene using deliberately different exposure settings.
Exposure fusion - Exposure fusion combines differently exposed images of a scene into a single display-oriented image by favoring useful content from each input.
Expressiveness - Expressiveness is the range of distinctions, relationships or conditions that a representation language can describe with its defined meaning.
Extended Boolean model - The extended Boolean model is an information-retrieval approach that combines structured Boolean-style queries with weighted matching and ranked results.
Extended Kalman filter - An extended Kalman filter, or EKF, estimates the evolving hidden state of a system whose dynamics or measurements are nonlinear.
Extended Kalman smoother - An extended Kalman smoother estimates past hidden states of a nonlinear dynamic system using observations collected both before and after those states.
Extendible hashing - Extendible hashing is a dynamic indexing method that uses selected bits of a key's hash value to locate a storage bucket through a directory.
Extension neural network - An extension neural network, or ENN, is a specialized pattern-recognition approach that combines neural-network ideas with extension theory, also called...
Extensional Component - The extensional component of a database or knowledge system is its collection of represented instances or facts, considered separately from the definitions...
Extensive form - Extensive form is a way of representing a game that explicitly describes the sequence of decisions, who makes them, what each player knows when choosing...
Extensive sampling - Extensive sampling describes sampling that emphasizes broad coverage across geography, subject matter, or time rather than concentrated investigation of a...
External Schema - An external schema describes the database information presented to a particular user group or application.
External validity - External validity is the extent to which findings from a study or evaluation apply beyond the particular conditions in which they were obtained.
Extraposition - Extraposition is a grammatical construction in which a clause or phrase appears later in a sentence than in a corresponding more basic arrangement.
Extremal Ensemble Learning - Extremal Ensemble Learning, or EEL, is a research approach that iteratively updates an ensemble of candidate solutions using their relative quality.
Extremal optimization - Extremal optimization is a heuristic search method that preferentially changes poorly performing components of a candidate solution.
Extrinsic evaluation - Extrinsic evaluation assesses an AI component or output by measuring its effect on a downstream task or wider application.
Extrusion detection - Extrusion detection is a security-monitoring perspective that looks for harmful activity originating inside a system or network, especially through outgoing...
Eye tracking - Eye tracking measures eye position or movement and often estimates where a person is looking over time.
F 1 - F1, sometimes written F 1 or F1 score, combines precision and recall through their harmonic mean.
F distribution - The F distribution is a continuous probability distribution obtained by taking the ratio of two independent chi-square random variables, each divided by its...
f-divergence - An f-divergence is a measure of difference between probability distributions generated by a chosen convex function f.
F-logic - F-logic, short for Frame Logic, is a formalism for representing and reasoning about objects, their properties, class membership and class relationships.
F-measure - F-measure is a family of evaluation scores that combine precision and recall into one number. The best-known member, F1, is their harmonic mean.
F-test of equality of variances - The F-test of equality of variances is a classical hypothesis test comparing the population variances underlying two independent normal samples.