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  2. Lazy evaluation - Wikipedia

    en.wikipedia.org/wiki/Lazy_evaluation

    Lazy evaluation can also lead to reduction in memory footprint, since values are created when needed. [19] In practice, lazy evaluation may cause significant performance issues compared to eager evaluation. For example, on modern computer architectures, delaying a computation and performing it later is slower than performing it immediately.

  3. Lazy initialization - Wikipedia

    en.wikipedia.org/wiki/Lazy_initialization

    In computer programming, lazy initialization is the tactic of delaying the creation of an object, the calculation of a value, or some other expensive process until the first time it is needed. It is a kind of lazy evaluation that refers specifically to the instantiation of objects or other resources.

  4. Evaluation strategy - Wikipedia

    en.wikipedia.org/wiki/Evaluation_strategy

    In a programming language, an evaluation strategy is a set of rules for evaluating expressions. [1] The term is often used to refer to the more specific notion of a parameter-passing strategy [2] that defines the kind of value that is passed to the function for each parameter (the binding strategy) [3] and whether to evaluate the parameters of a function call, and if so in what order (the ...

  5. Lazy learning - Wikipedia

    en.wikipedia.org/wiki/Lazy_learning

    In machine learning, lazy learning is a learning method in which generalization of the training data is, in theory, delayed until a query is made to the system, as opposed to eager learning, where the system tries to generalize the training data before receiving queries.

  6. Graph reduction - Wikipedia

    en.wikipedia.org/wiki/Graph_reduction

    Combinator graph reduction is a fundamental implementation technique for functional programming languages, in which a program is converted into a combinator representation which is mapped to a directed graph data structure in computer memory, and program execution then consists of rewriting parts of this graph ("reducing" it) so as to move towards useful results.

  7. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.

  8. Python syntax and semantics - Wikipedia

    en.wikipedia.org/wiki/Python_syntax_and_semantics

    Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers:

  9. Fixed-point combinator - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_combinator

    In a language that supports lazy evaluation, like in Haskell, it is possible to define a fixed-point combinator using the defining equation of the fixed-point combinator which is conventionally named fix. Since Haskell has lazy datatypes, this combinator can also be used to define fixed points of data constructors (and not only to implement ...