LeetCode: Longest Increasing Subsequence Solution

Dynamic programming, top-down approach

Approach

recursion(i)
returns the longest increasing subsequence of
nums.slice(0, i)

  • base case:
    1
    for
    i === 0
    (only one element)
  • max(1 + recursion(j))
    for every
    j < i
    and
    nums[j] < nums[i]

Final result will be

max(recursion(i))
all over
i

Implementation

1/**
2 * @param {number[]} nums
3 * @return {number}
4 */
5var lengthOfLIS = function (nums) {
6 const n = nums.length
7 const memo = Array(n).fill(null)
8
9 const recursion = i => {
10 if (i === 0) {
11 return 1
12 }
13
14 if (memo[i] !== null) {
15 return memo[i]
16 }
17
18 let res = 1
19
20 for (let j = 0; j < i; j++) {
21 if (nums[j] < nums[i]) {
22 res = Math.max(res, 1 + recursion(j))
23 }
24 }
25
26 return (memo[i] = res)
27 }
28
29 let res = 0
30
31 for (let i = 0; i < n; i++) {
32 res = Math.max(res, recursion(i))
33 }
34
35 return res
36}

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Tags

leetcode

recursion

dynamic programming

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