Expectiminimax value - An expectiminimax value is the value assigned to a game-tree position by combining maximizing choices, minimizing choices, and probability-weighted chance...
Experience replay - Experience replay is a training technique where a reinforcement learning agent stores its past experiences and repeatedly trains on random samples of them...
Experiment - An experiment is a planned investigation in which a researcher deliberately changes one or more conditions and observes the resulting outcomes.
Experimental benchmarking - Experimental benchmarking compares estimates from a nonexperimental research method with estimates from an experiment addressing a comparable causal question.
Experimental Studies - Experimental studies investigate the effects of deliberately applied treatments or conditions on measured outcomes.
Experimenter's bias - Experimenter's bias is a systematic influence on a study's procedures, observations, analysis, or interpretation arising from the researcher's expectations...
Expert system - An expert system is a computer program designed to apply specialized knowledge to problems within a defined domain.
Expit - Expit is another name for the logistic sigmoid function, which maps a real number to a value between zero and one.
Explainable AI - Explainable AI, often abbreviated XAI, is the study and practice of making AI systems and their outputs understandable to people through suitable...
Explainable empirical risk minimization - Explainable empirical risk minimization, or EERM, is a research approach that adds a user-related explainability objective to ordinary empirical risk...
Explained variance score - The explained variance score is a regression evaluation metric defined, for a target with positive variance, as one minus the variance of prediction errors...
Explained variation - Explained variation is the part of variation in an outcome that is accounted for by a specified statistical model or set of predictors.
Explainer - An explainer is a method, component, or tool that produces explanations of an AI system's behavior.
Explanation - An explanation is an account that helps someone understand an AI system, its output, or a relevant aspect of its behavior.
Explanation-based learning - Explanation-based learning, or EBL, uses existing domain knowledge to explain an example and derive a reusable rule from that explanation.
Explanatory model - An explanatory model represents an outcome as related to one or more other variables.
Explicit multi-threading - Explicit Multi-Threading, or XMT, is a research framework for parallel computer architecture and programming developed around the parallel random-access...
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.