Exact algorithm - An exact algorithm is an algorithm that solves the specified problem correctly rather than returning an approximation.
Exact cell decomposition - Exact cell decomposition is a motion-planning approach that partitions the collision-free configuration space into cells while preserving its relevant...
Exact match - Exact match is an evaluation rule that gives credit only when a prediction equals an accepted reference answer under the specified comparison procedure.
Exact test - An exact test is a hypothesis test calibrated using a finite-sample null distribution rather than relying on a large-sample approximation.
Example-based machine translation - Example-based machine translation, or EBMT, translates new input by retrieving relevant bilingual examples and adapting their target-language counterparts.
Exclusion Bias - Exclusion bias arises when relevant people, groups, or cases are left out of data collection, testing, or analysis in a way that distorts the resulting...
Excursion probability - An excursion probability is the probability that a random process exceeds a specified level somewhere within a defined observation domain.
Execution - Execution is the process of carrying out selected actions or instructions.
Execution monitoring - Execution monitoring is the process of observing an agent's actions and environment during plan execution to determine whether the current course of action...
Execution plan - An execution plan is a database's description of the operations it intends to use, or has used, to answer a query.
Exemplar inpainting (Criminisi) - Exemplar inpainting, in the Criminisi approach, fills a selected missing or unwanted image region by copying suitable patches from an available source region.
Exhaustive decomposition - An exhaustive decomposition describes a category using subcategories whose combined membership covers the whole category.
Existence-Based Identity - Existence-based identity describes object identity that is independent of an object's current attribute values.
Existence uncertainty - Existence uncertainty is uncertainty about whether a modeled object, event, or relationship actually exists.
Existential graphs - Existential graphs are a diagrammatic system of logic developed by Charles Sanders Peirce.
Existential risk - Existential risk is the possibility of an outcome that destroys humanity or permanently and drastically limits humanity's future potential.
Exogenous variable - An exogenous variable is a variable whose value is treated as determined outside the model or system being analyzed.
Expand (pyramid operator) - Expand is an image-pyramid operator that maps a smaller image level onto a larger sampling grid, typically doubling each spatial dimension and applying an...
Expander walk sampling - Expander walk sampling is a method of generating useful samples by following a random walk on a suitably well-connected graph called an expander.
Expectation conditional maximization - Expectation conditional maximization (ECM) is a variant of the expectation-maximization algorithm that replaces a difficult joint maximization step with...
Expectation-maximization - Expectation-maximization, usually abbreviated EM, is an iterative method for estimating model parameters when some relevant information is unobserved.
Expectation propagation - Expectation propagation, or EP, is an approximate Bayesian inference method that replaces difficult probability factors with simpler approximations and...
Expected calibration error - Expected calibration error (ECE) is a summary measure of how closely a classifier's stated confidence matches its observed correctness.
Expected frequencies - Expected frequencies are the counts predicted for categories or table cells by a specified probability model, often the null hypothesis in a statistical test.
Expected improvement - Expected improvement (EI) is a Bayesian optimization acquisition function that measures the model-predicted average amount by which evaluating a candidate...
Expected monetary value - Expected monetary value, or EMV, is the probability-weighted average of possible monetary outcomes.
Expected SARSA - Expected SARSA is a temporal-difference method that updates an action-value estimate using the policy-weighted average of the next state's action values.
Expected utility - Expected utility is the probability-weighted average of the utility assigned to possible outcomes.
Expected value - Expected value is the probability-weighted average of a numerical quantity's possible values. It is also called the mean or expectation.
Expectiminimax - Expectiminimax is a game-tree search method that extends minimax to include random events.
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...