Social data science - Social data science combines computational and statistical methods with social-science theory and research design to study people, relationships...
Social laws - In multiagent AI, social laws are shared rules or conventions that constrain agents' behavior so that they can operate together more predictably.
Social media mining - Social media mining is the use of computational and analytical methods to discover patterns in social-media content, activity and relationships.
Social profiling - Social profiling is the construction of a representation of a person or account from social data, including stated information, online activity and...
Social sorting - Social sorting is the classification of people or populations into categories that influence how they are treated, what opportunities they receive or what...
Societal Bias - Societal Bias refers to patterns of favoring or disfavoring people or groups based on social identities, demographic characteristics, or socially embedded...
Socio-technical system - A socio-technical system is a system whose behavior and outcomes arise from interacting social and technical elements.
Soft actor-critic - Soft actor-critic, or SAC, is an off-policy actor-critic reinforcement-learning algorithm that optimizes expected reward together with a policy-entropy term.
Soft clustering - Soft clustering describes an item using degrees of membership in several clusters instead of assigning it only to one group.
Soft independent modeling of class analogies - Soft independent modeling of class analogies, usually abbreviated SIMCA, is a class-modeling approach that builds a separate principal-component model for...
Soft label - A soft label is a target that assigns weights or probabilities across classes instead of selecting only one class.
Soft margin - A soft margin is the allowance for penalized margin violations in a support vector classifier.
Soft prompt tuning - Soft prompt tuning adapts a pretrained model by learning a small set of continuous prompt vectors while keeping the base model's weights fixed.
Softmax - Softmax converts a list of numerical scores into positive values that sum to one.
Softplus Function - The Softplus function is a smooth activation function defined by softplus(x) = ln(1 + exp(x)).
Softsign Function - The Softsign function is a neural-network activation defined by softsign(x) = x/(1 + |x|), where |x| means the absolute value of x.
Software agent - A software agent is a software system that acts within an environment on behalf of a user or another system, with some degree of autonomy.
Software architecture - Software architecture is the organization of a software system's major parts, their responsibilities, and the ways they interact.
Software mining - Software mining is the extraction and analysis of information from software and its development or operational records to understand systems, discover...
Software testing - Software testing is a set of activities used to evaluate software and related work products, discover defects and provide evidence about whether...
Solid compression - Solid compression compresses data from several files together within a shared compression stream or block, allowing information from one file to help encode...
Solomon four-group design - The Solomon four-group design is a randomized experimental design that crosses an intervention with the presence or absence of a pretest.
Solomonoff's theory of inductive inference - Solomonoff's theory of inductive inference is a mathematical framework for predicting future observations by combining computable explanations of past...
Sort Operation - A sort operation arranges records according to one or more comparison keys and directions.
Soundex - Soundex is a phonetic indexing method that groups selected spelling variants under a short code.
Source-filter model - The source-filter model explains speech as an excitation signal shaped by the acoustic response of the vocal tract.
SOV language - An SOV language is a language whose basic or dominant clause order places the subject before the object and the object before the verb.
Span - In natural language processing, a span is a selected stretch of text identified by its boundaries.
Span-corruption language-model objective - A span-corruption language-model objective trains a model to reconstruct consecutive pieces of text removed from an input.
Spanning Trees - A spanning tree of a connected, undirected graph is a selection of its edges that connects every vertex without creating a cycle.
Sparse Auto Encoder - A sparse autoencoder is a neural network trained to reconstruct its input while encouraging a sparse internal representation.
Sparse binary polynomial hashing - Sparse binary polynomial hashing, or SBPH, is a text-feature generation technique associated with the CRM114 classifier.
Sparse feature - A sparse feature is a feature whose expanded representation contains mostly zeros or inactive values.
Sparse Fourier transform - A sparse Fourier transform is an algorithmic approach that exploits a signal's sparse or approximately sparse frequency representation to recover its...
Sparse graph - A sparse graph is a graph with relatively few edges compared with the number of possible connections among its vertices.
Sparse Learning - Sparse learning is a family of machine-learning approaches that favor models or representations in which relatively few components are nonzero or active.
Sparse matrix - A sparse matrix is a two-dimensional numerical array in which most entries are zero.
Sparse model - A sparse model is a model whose representation contains relatively few active or nonzero components compared with the available possibilities.
Sparse PCA - Sparse PCA is a family of principal-component methods that encourage each component to depend on relatively few original variables.
Sparse representation - A sparse representation records data using relatively few active values compared with the number of possible positions or components.
Sparse variational Gaussian process - A sparse variational Gaussian process is an approximate Gaussian process model that represents posterior information using a smaller set of inducing...
Sparse vector - A sparse vector is a vector in which most entries are zero.
Sparsity - Sparsity describes how much of a numerical representation consists of zero entries.
Sparsity-of-effects principle - The sparsity-of-effects principle is the working expectation that only a relatively small subset of the many possible effects in an experiment materially...
Spatial Analysis of Principal Components - Spatial analysis of principal components, commonly called spatial PCA or sPCA, is a multivariate method that combines variation in measurements with spatial...
Spatial architecture - A spatial architecture is a computing organization that distributes operations across connected processing elements, mapping a computation's dataflow onto...
Spatial embedding - A spatial embedding is a numerical representation of spatial information designed for use in a learning or analysis system.
Spatial frequency - Spatial frequency describes how rapidly a pattern varies across space, often measured as cycles per unit distance or per degree of visual angle.