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Approach 1: Sliding Window
Intuition
We can rephrase this as a problem about the prefix sums of A. Let P[i] = A[0] + A[1] + ... + A[i-1]. We want the smallest y-x such that y > x and P[y] - P[x] >= K.
Motivated by that equation, let opt(y) be the largest x such that P[x] <= P[y] - K. We need two key observations:
If
x1 < x2andP[x2] <= P[x1], thenopt(y)can never bex1, as ifP[x1] <= P[y] - K, thenP[x2] <= P[x1] <= P[y] - Kbuty - x2is smaller. This implies that our candidatesxforopt(y)will have increasing values ofP[x].If
opt(y1) = x, then we do not need to consider thisxagain. For if we find somey2 > y1withopt(y2) = x, then it represents an answer ofy2 - xwhich is worse (larger) thany1 - x.
Algorithm
Maintain a "monoqueue" of indices of P: a deque of indices x_0, x_1, ... such that P[x_0], P[x_1], ... is increasing.
When adding a new index y, we'll pop x_i from the end of the deque so that P[x_0], P[x_1], ..., P[y] will be increasing.
If P[y] >= P[x_0] + K, then (as previously described), we don't need to consider this x_0 again, and we can pop it from the front of the deque.
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