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  2. Conflict-free replicated data type - Wikipedia

    en.wikipedia.org/wiki/Conflict-free_replicated...

    State-based CRDTs (also called convergent replicated data types, or CvRDTs) are defined by two types, a type for local states and a type for actions on the state, together with three functions: A function to produce an initial state, a merge function of states, and a function to apply an action to update a state. State-based CRDTs simply send ...

  3. Propagation constraint - Wikipedia

    en.wikipedia.org/wiki/Propagation_constraint

    In database systems, a propagation constraint "details what should happen to a related table when we update a row or rows of a target table" (Paul Beynon-Davies, 2004, p.108). Tables are linked using primary key to foreign key relationships.

  4. Connection pool - Wikipedia

    en.wikipedia.org/wiki/Connection_pool

    In software engineering, a connection pool is a cache of reusable database connections managed by the client or middleware. It reduces the overhead of opening and closing connections, improving performance and scalability in database applications.

  5. Lagrange multiplier - Wikipedia

    en.wikipedia.org/wiki/Lagrange_multiplier

    The Lagrange multiplier theorem states that at any local maximum (or minimum) of the function evaluated under the equality constraints, if constraint qualification applies (explained below), then the gradient of the function (at that point) can be expressed as a linear combination of the gradients of the constraints (at that point), with the ...

  6. Lambda architecture - Wikipedia

    en.wikipedia.org/wiki/Lambda_architecture

    The two view outputs may be joined before presentation. The rise of lambda architecture is correlated with the growth of big data, real-time analytics, and the drive to mitigate the latencies of map-reduce. [1] Lambda architecture depends on a data model with an append-only, immutable data source that serves as a system of record.

  7. Constrained conditional model - Wikipedia

    en.wikipedia.org/wiki/Constrained_conditional_model

    The constraint can be used as a way to incorporate expressive [clarification needed] prior knowledge into the model and bias the assignments made by the learned model to satisfy these constraints. The framework can be used to support decisions in an expressive output space while maintaining modularity and tractability of training and inference.

  8. Karush–Kuhn–Tucker conditions - Wikipedia

    en.wikipedia.org/wiki/Karush–Kuhn–Tucker...

    Consider the following nonlinear optimization problem in standard form: . minimize () subject to (),() =where is the optimization variable chosen from a convex subset of , is the objective or utility function, (=, …,) are the inequality constraint functions and (=, …,) are the equality constraint functions.

  9. Constraint satisfaction problem - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction...

    Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables , which is solved by constraint satisfaction methods.