Memoization vs. Memorization — What's the Difference?

Optimizes recursive functions.

Learning technique.

Used to avoid repeated calculations.

Applied in academic learning.

Enhances performance of algorithms.

Used to retain a large amount of information.

Stores results based on input parameters.

Can be enhanced with mnemonic devices.

Caching technique in computing.

Involves repetition and recall.

In computing, memoization or memoisation is an optimization technique used primarily to speed up computer programs by storing the results of expensive function calls and returning the cached result when the same inputs occur again. Memoization has also been used in other contexts (and for purposes other than speed gains), such as in simple mutually recursive descent parsing.

Memorization is the process of committing something to memory. It is a mental process undertaken in order to store in memory for later recall visual, auditory, or tactical information.

(computer science) A technique in which partial results are recorded (forming a memo) and then can be re-used later without having to recompute them.

To commit to memory; learn by heart.

The act of committing something to memory or memorizing.

Learning so as to be able to remember verbatim;

Memoization is most effective in algorithms that repeatedly calculate the same results, such as dynamic programming and recursive functions.

Memorization involves storing facts and data, often without understanding underlying concepts, while understanding requires comprehension and the ability to apply knowledge.

Memoization is used to optimize programs by caching results of expensive function calls to avoid repeated calculations.

Problems with overlapping subproblems and optimal substructure, such as many dynamic programming problems.

It reduces the number of computations by reusing previously calculated results, thus speeding up program execution.

Effective techniques include spaced repetition, the use of mnemonic devices, and active recall practice.

Tools include programming libraries and built-in language features that facilitate caching mechanisms.

Memorization helps in retaining essential facts and data that can be critical for academic tests and practical application.

Memoization can increase memory usage significantly, which might not be optimal for memory-constrained environments.

Educational systems vary in their emphasis on memorization; some prioritize rote learning, while others focus more on conceptual understanding.

Excessive reliance on memorization without understanding can hinder deeper learning and the ability to apply knowledge creatively.

Educators can enhance memorization by incorporating various sensory learning methods, practical applications, and regular review sessions.

Memoization is typically implemented by storing function outputs in a hashmap or dictionary keyed by arguments.

Memorization is crucial in subjects like biology, history, and languages, where large amounts of factual information are needed.

An example is using the acronym "HOMES" to remember the Great Lakes: Huron, Ontario, Michigan, Erie, and Superior.