Imieliński - Lipski algebra - Imieliński - Lipski algebra refers to a family of theoretical treatments that extend relational querying to databases containing incomplete information.
Imitation learning - Imitation learning is a family of methods that learn how to perform a task from demonstrations of another agent's behavior.
Immutable Data Types - Immutable data types are types whose objects do not support changes to their own value after creation.
Impact assessment - An impact assessment is a structured examination of how a proposed or operating system may affect people, organizations, society, or the environment.
Impartial culture - Impartial culture is a probability model for preferences in which each participant independently selects a complete strict ranking uniformly from all...
Impedance Mismatch - Impedance mismatch in database work describes friction between different data models or programming environments.
Imperfect information - Imperfect information is a condition in a game where a player making a decision cannot distinguish all relevant situations that may have occurred.
Impersonation - Impersonation is presenting oneself, a message, or a system as another person or trusted entity.
Implementation level - The implementation level describes the concrete mechanisms that make an information-processing system operate.
Implication - An implication is a logical statement of the form “if P, then Q,” written P → Q. P is its antecedent and Q its consequent.
Implicature - An implicature is something a speaker communicates indirectly, beyond what the utterance explicitly says.
Implicit argument - An implicit argument is a participant associated with a predicate's meaning that is not overtly expressed in the relevant phrase or clause.
Implicit bias - Implicit bias refers to automatic associations or assumptions that can influence how someone interprets information or makes a judgment without deliberate...
Implicit curve - An implicit curve in the plane is described by a relation such as F(x,y)=0, rather than by explicitly expressing one coordinate as a function of the other.
Implicit data collection - Implicit data collection is the gathering of behavioral traces that can be used to infer user interests, preferences or needs without asking for a direct...
Implicit Language Model - An Implicit Language Model is language-pattern knowledge learned within a broader system without being supplied as a separate, explicitly integrated...
Implicit models - Implicit models, in probabilistic modeling, specify a procedure for generating samples rather than relying on an explicitly evaluable probability mass or...
Implicit neural network layer - An implicit neural network layer defines its output through conditions that the output must satisfy, such as an equation, fixed point or optimization problem.
Implicit parallelism - Implicit parallelism is parallel execution that a compiler, runtime or execution system discovers or manages without the programmer spelling out every...
Implicit surface - An implicit surface represents a three-dimensional boundary as the set of points satisfying an equation such as F(x,y,z)=0.
Importance sampling - Importance sampling is a Monte Carlo technique that estimates quantities under one probability distribution by drawing samples from another and correcting...
Importance-weighted evidence lower bound - An importance-weighted evidence lower bound is a variational objective formed by taking the expected logarithm of an average of importance weights.
Impulse (delta) - An impulse, or delta, is an idealized localized input used in signal and image processing.
Impulse response weights - Impulse response weights describe how a dynamic model's output responds over successive time lags to a one-time unit input or shock.
Imputation variance - Imputation variance is the component of an estimate's variability associated with replacing missing or unusable observations by imputed values.
In-crowd algorithm - The In-crowd algorithm is an active-set method for solving an L1-regularized least-squares problem, commonly called basis pursuit denoising.
In-group bias - In-group bias is partiality toward people who belong to one's own group or share one's own characteristics.
In-processing - In-processing is a family of fairness-mitigation approaches that change how a machine-learning model is trained.
In-set condition - An in-set condition is a constraint or test that checks whether a case belongs to the set the model was built for: inside the population, ranges and...
Inadmissible heuristic - An inadmissible heuristic is a search estimate that overestimates the true minimum remaining cost for at least one relevant state.
Inauthentic text - Inauthentic text, in a specific strand of text-analysis research, means syntactically well-formed writing that lacks meaning as a whole.
Incident - An incident is an event or connected set of events that meets an organization's or framework's criteria for requiring investigation and response because...
Incident response - Incident response is the coordinated work of investigating an incident, limiting its effects, addressing the problem, and restoring an acceptable operating...
Inclusion-exclusion principle - The inclusion-exclusion principle calculates the size of a union of overlapping sets, or the probability that at least one of several events occurs.
Incompatibility of fairness metrics - Incompatibility of fairness metrics means that some mathematical fairness conditions cannot all be satisfied simultaneously under particular data and...
Incomplete join - Incomplete join is an informal description of a join whose conditions do not fully specify the intended relationship between its inputs.
Incompleteness theorem - An incompleteness theorem establishes limits on what certain formal mathematical systems can prove.
Incremental belief-state search - Incremental belief-state search builds a plan by considering possible physical states progressively.
Incremental encoding - In string compression, incremental encoding represents a string partly through shared content with a preceding string, commonly storing their common-prefix...
Incremental Few-shot Learning - Incremental few-shot learning is learning new categories or capabilities in successive stages from small labeled datasets while retaining useful performance...
Incremental heuristic search - Incremental heuristic search solves a sequence of related search problems by reusing information from earlier searches and using a heuristic to guide the work.
Indefinite reference - Indefinite reference is the use of an expression, often a noun phrase such as “a technician” or “some packages,” without presenting its referent as already...
Independence - Independence, in probability, means that knowing one event or variable does not change the probability information about another.
Independence Metropolis sampler - An independence Metropolis sampler is a Metropolis - Hastings algorithm that proposes each candidate from a fixed distribution independent of the chain's...
Independent component analysis - Independent component analysis is a statistical method for expressing observed data as mixtures of underlying components that are as statistically...
Independent Events - Independent events are events for which the probability of their joint occurrence equals the product of their individual probabilities: P(A and B) = P(A)...
Independent multivalued fact - An independent multivalued fact is a set of values associated with an entity that varies independently of another set associated with that same entity.
Independent subproblems - Independent subproblems are parts of a larger problem that can be solved separately and whose solutions can be combined without additional compatibility...