kQP

kQP is an acronym that can refer to several concepts across different fields. There is no single, universally accepted meaning, and the intended interpretation is usually clear from context.

In mathematics and machine learning, kQP commonly denotes Kernel Quadratic Programming. This refers to a class of optimization problems that extend standard quadratic programming by employing kernel functions to map inputs into a high-dimensional feature space. The objective remains quadratic, but the kernel trick allows nonlinear relationships to be captured without explicit feature expansion. Kernel Quadratic Programming appears in various machine learning tasks, including regularized regression and support vector machines, where the solution is found in a dual form that depends on kernel evaluations.

In information science and knowledge management, kQP can stand for Knowledge Query Protocol. This term describes a framework for querying distributed or heterogeneous knowledge bases with attention to query semantics, provenance, and consistency. Implementations may specify query languages, result reconciliation strategies, and metadata to track data quality or source reliability. Because "kQP" is not universally standardized, specific definitions vary by project or publication.

Because the term is ambiguous, readers are advised to rely on contextual cues to determine which interpretation applies. If a particular domain or document uses kQP, the surrounding text often outlines the intended meaning, or there may be an explicit definition early in the material.