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Probabilistic Soft Logic (PSL) is a statistical relational learning (SRL) framework for modeling probabilistic and relational domains. [2] It is applicable to a variety of machine learning problems, such as collective classification, entity resolution, link prediction, and ontology alignment.
Branch prediction attempts to guess whether a conditional jump will be taken or not. Branch target prediction attempts to guess the target of a taken conditional or unconditional jump before it is computed by decoding and executing the instruction itself. Branch prediction and branch target prediction are often combined into the same circuitry.
An indirect branch (also known as a computed jump, indirect jump and register-indirect jump) is a type of program control instruction present in some machine language instruction sets.
The input–process–output (IPO) model, or input-process-output pattern, is a widely used approach in systems analysis and software engineering for describing the structure of an information processing program or other process.
PPLs often extend from a basic language. For instance, Turing.jl [12] is based on Julia, Infer.NET is based on .NET Framework, [13] while PRISM extends from Prolog. [14] However, some PPLs, such as WinBUGS, offer a self-contained language that maps closely to the mathematical representation of the statistical models, with no obvious origin in another programming language.
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This can be seen as a structured prediction problem [2] in which the structured output domain is the set of all possible parse trees. Structured prediction is used in a wide variety of domains including bioinformatics , natural language processing (NLP), speech recognition , and computer vision .
Use of futures may be implicit (any use of the future automatically obtains its value, as if it were an ordinary reference) or explicit (the user must call a function to obtain the value, such as the get method of java.util.concurrent.Futurein Java). Obtaining the value of an explicit future can be called stinging or forcing. Explicit futures ...