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Tag: memoization

Memoize a recursive Fibonacci function

I created a withMemo function that returns a memoized version of the provided function. How can I memoize this fibonacci function that works with recursion ? Indeed withMemo(fibo) doesn’t improve performance since the recursive calls inside fibo still point to the unmemoized version… So I have to alter the declaration of fibo to make momoization work: Is there a way

Why does howSum solution work in Javascript but not in Python? (Dynamic programming)

This is a follow-up to this question asked on Stack Overflow. Write a function ‘howSum(targetSum, numbers)’ that takes in a targetSum and an array of numbers as arguments. The function should return an array containing any combination of elements that add up to exactly the targetSum. If there is no combination that adds up to the targetSum, then return None.

memoizee – Cached based on arguments

I would like to memoize results of function based on provided arguments. For example: This invocations should be independent and should have standalone cached results. Currently I always receive the result from the first call. I tried used other library than memoizee. With fast-memoize I got expected effect, but fast-memoize doesn’t allow set maxAge of cached results. In second call

Javascript factorial function memoization

I’m trying to use the factorial function with memoization. I have taken the max value from the object to reduce the number of recursive calls made. But the problem is the first call is I don’t know whether this is optimized or not since the first call is pretty expensive. Any insights on this will be great. Answer You don’t

Memoize a curried function

Is it possible to memoize f with regard to the 2 arguments, namely: Answer You could take a Map as cache and take nested maps for all following arguments. This cache works for arbitrary count of arguments and reuses the values from the former calls. It works by taking a curried function and an optional Map. If the map is

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