memoization

问题 Description Given a dictionary, my program generates two output files, 'sequences.txt' and 'words.txt'. 'sequences' contain every sequence of four letters (A-z) that appear in exactly one word of the dictionary, one sequence per line. 'words' will contain the corresponding words that contain the sequences, in the same order, again one per line. For example, given spec/fixtures/sample_words.txt dictionary containing only arrows carrots give me The outputs should be: 'sequences' 'words' carr

问题 This is a classical game where two players play following game: There are n coins in a row with different denominations. In this game, players pick a coin from extreme left or extreme right (they blindly pick from any extreme with a probability of .5, both of them are dumb). I just want to count the expected sum of player who starts the game. For this I want to sum up all the possible combinations of values a player can have. I am using a recursive solution which sums up all the possible

问题 I try running: cabal install memoize in the Terminal but all I get is: 11 warnings and 1 error generated. Failed to install memoize-0.6 cabal: Error: some packages failed to install: memoize-0.6 failed during the building phase. The exception was: ExitFailure 1 The 1 error is: Data/Function/Memoize/TH.hs:5:6: error: invalid preprocessing directive #-} ^ 来源： https://stackoverflow.com/questions/23595173/invalid-preprocessing-directive-when-installing-memoize

问题 module Main where import System.Random import Data.Foldable import Control.Monad import qualified Data.Map as M import qualified Data.Vector as V import Debug.Trace import Data.Maybe import Data.Ord -- Represents the maximal integer. maxBound is no good because it overflows. -- Ideally should be something like a billion. maxi = 1000 candies :: V.Vector Int -> Int --M.Map (Int, Int) Int candies ar = ff [l (V.length ar - 1) x | x <- [0..maxi]] where go :: Int -> Int -> Int go _ 0 = maxi go 0 j

问题 ...or are there better ways to implement a Memoization? Function.memoize = function(callableAsString) { var r = false, callable, code; try { callable = eval(callableAsString); if (typeof callable == "function" && typeof(Function.memoize.cache[callableAsString]) == "undefined") { code = callableAsString + " = function()" + "{" + "var cache = Function.memoize.cache['" + callableAsString + "'];" + "var k = Json.stringify([this].concat(arguments));" + "return cache.r[k] || (cache.r[k] = cache.c

问题 I'm making a program that calculates a combination given two numbers, ex: java Combination 5 3 would give an answer of 10. I have a method that looks like this: public static int choose(int n, int k) { // chooses k elements out of n total if (n == 0 && k > 0) return 0; else if (k == 0 && n >= 0) return 1; else return choose(n - 1, k - 1) + choose(n - 1, k); How would I be able to use memoization for this in order to make it calculate faster with larger numbers? 回答1: You might be better off

问题 i'm trying to cache the return value of a function only in case it's not None. in the following example, it makes sense to cache the result of someFunction in case it managed to obtain data from some-url for an hour. if the data could not be obtained, it does not make sense to cache the result for an hour (or more), but probably for 5 minutes (so the server for some-domain.com has some time to recover) def _cachekey(method, self, lang): return (lang, time.time() // (60 * 60)) @ram.cache(

问题 Given a string consisting of only vowels, find the longest subsequence in the given string such that it consists of all five vowels and is a sequence of one or more a’s, followed by one or more e’s, followed by one or more i’s, followed by one or more o’s and followed by one or more u’s. If there is more than one longest subsequence, print any one. QUESTION: can u pls show how u would add memoization to soln below/show how to solve using dp? I've seen how to solve recursively (below). I'm

问题 Looking at React's useMemo documentation. They say to use it when you need to compute an expensive calculation. This optimization helps to avoid expensive calculations on every render. I looked at the memoized link they provide and what I understood is that you can think of it like an cache. I'm not an expert at computer science, but I know that memoization is a good optimization for calculating fibonacci I'm still trying to understand better why and how to use useMemo , but a few things are

问题 I'd like to do a TTL based memoization with active refresh asynchronously in scala. ScalaCache example in the documentation allows for TTL based memoization as follows: import scalacache._ import memoization._ implicit val scalaCache = ScalaCache(new MyCache()) def getUser(id: Int): User = memoize(60 seconds) { // Do DB lookup here... User(id, s"user${id}") } Curious whether the DB lookup gets triggered after TTL expires for existing value, synchronously and lazily during the next getUser