Subgradient descent - Subgradient descent is an iterative optimization method that replaces an ordinary gradient with a subgradient.
Subgraph isomorphism - Subgraph isomorphism asks whether a smaller pattern graph can be matched to part of a larger graph while preserving the required connections.
Subgroup analysis - Subgroup analysis examines results separately for defined subsets of a study population or dataset.
Subject indexing - Subject indexing is the process of describing what an information resource is about through assigned terms, headings, codes, or other subject indicators.
Subject-verb agreement - Subject-verb agreement is the grammatical relationship in which a verb's form matches relevant features of its subject, such as person and number.
Subjective logic - Subjective logic is a formal framework for reasoning with uncertain opinions, developed by Audun Jøsang.
Subjective probability - Subjective probability expresses an individual's or agent's degree of belief that a proposition is true, given the information and assumptions available to...
Subjectivity - In language analysis, subjectivity is the expression of a person’s perspective, evaluation, opinion, emotion, belief, or related private state.
Submodular optimization - Submodular optimization seeks to minimize or maximize a set-valued objective with a diminishing-returns property.
Submodularity - Submodularity is a mathematical property of a set function that expresses diminishing marginal returns.
Subproblem - A subproblem is a smaller problem defined within the process of solving a larger one.
Subset of regressors Gaussian process approximation - The subset of regressors Gaussian process approximation, or SoR, replaces a full Gaussian process covariance with a finite-rank covariance determined by a...
Subsetting - Subsetting is selecting and retrieving a specified portion of a larger dataset or data object.
Subspace - A subspace is a subset of a vector space that is itself a vector space under the same addition and scalar multiplication.
Subspace Gaussian mixture model - A subspace Gaussian mixture model, or SGMM, is an acoustic-modeling approach for speech recognition that shares a structured Gaussian-mixture representation...
Subspace identification - Subspace identification is a family of methods for estimating dynamical state-space models from observed time-series data using matrix projections and...
Substitutability - In syntactic analysis, substitutability is the possibility of replacing one word or group of words with another expression in a grammatical environment.
Subsumption - Subsumption is a formal relationship in which one expression covers another under a specified notion of generality.
Subsumption architecture - Subsumption architecture is a robot-control approach that builds increasingly capable behavior from concurrently operating layers.
Subsumption lattice - A subsumption lattice organizes symbolic expressions by how general or specific they are under substitution.
Subvocal recognition - Subvocal recognition is the computational recognition of deliberately produced silent or nearly silent speech-related activity.
Subword Segmentation - Subword segmentation divides text into reusable pieces that may be smaller than complete words.
Subword token - A subword token is a unit of text used by a tokenizer that can represent part of a word, a whole word, or another learned text fragment.
Subwords - Subwords are text units smaller than a whole word that can be used as tokens in language-processing systems.
Successor-state axiom - A successor-state axiom is a logical rule that specifies exactly when a changing property is true after an action.
Sufficient dimension reduction - Sufficient dimension reduction seeks a smaller representation of predictors that preserves all their information about a specified response.
Sufficient statistic - A sufficient statistic is a function of observed data that preserves all the information those data contain about a specified parameter within a specified...
Sugeno integral - The Sugeno integral is an aggregation method that combines ordered input scores using minimum and maximum operations and a monotone set function called a...
Sum of squared differences - Sum of squared differences, often shortened to SSD, is a numerical measure obtained by subtracting corresponding values in two equally sized sets, squaring...
Sum-of-squares optimization - Sum-of-squares optimization, or SOS optimization, uses representations of polynomials as sums of squared polynomials to obtain tractable certificates of...
Sums of squares - Sums of squares are totals formed by squaring quantities, commonly deviations from a mean, fitted value, or other reference, and adding the results.
Sunburst chart - A sunburst chart displays hierarchical data as sectors arranged in concentric rings.
Sunk Cost Fallacy Bias - Sunk cost fallacy bias is the tendency to let irrecoverable past expenditure justify continuing an activity, even when its remaining costs and benefits do...
Sunrise problem - The sunrise problem asks how observing an event repeatedly should affect belief that it will happen again.
Super column - A super column is a named grouping of ordinary columns in Cassandra's historical data model.
Super learner - Super learner is an ensemble-learning approach that uses cross-validation to select or combine predictions from a library of candidate algorithms according...
Super-resolution - Super-resolution is the task of estimating a higher-resolution image from one or more lower-resolution observations.
Superintelligence ban - A superintelligence ban is a proposed prohibition on developing, deploying, or otherwise enabling AI systems that exceed a defined superintelligence threshold.
Superiority and inferiority ranking method - The superiority and inferiority ranking method, usually abbreviated SIR, is a family of methods for comparing alternatives across several criteria.
Superkey - A superkey is a set of attributes whose combined values uniquely identify a tuple in every permitted instance of a relation.
Superpixels - Superpixels are small image regions formed by grouping nearby pixels with similar properties, often color or brightness.
Superquadrics - Superquadrics are a family of parameterized three-dimensional shapes that generalize familiar forms such as ellipsoids.
Supervised Biclustering - Supervised biclustering identifies related groups of rows and columns in a data matrix while using labels, outcomes or other supervising information to...
Supervised Clustering - Supervised clustering groups objects using guidance from known labels.
Supervised fine-tuning - Supervised fine-tuning, or SFT, adapts an already trained model using examples that specify the desired output for an input.
Supervised learning - Supervised learning trains a model using examples that pair inputs with known target outputs.
Supervised principal component analysis - Supervised principal component analysis uses outcome information to guide a lower-dimensional representation of predictors.
Support vector machine - A support vector machine, or SVM, is a learning method that can build a decision boundary between classes while balancing separation against errors.