Given an array of integers size N, how can you efficiently find a subset of size K with elements that are closest to each other?

Let the closeness for a subset (x1,x2,x3,..xk) be defined as:

2 <= N <= 10^5

2 <= K <= N

constraints: Array may contain duplicates and is not guaranteed to be sorted.

My brute force solution is very slow for large N, and it doesn't check if there's more than 1 solution:

N = input()
K = input()
assert 2 <= N <= 10**5
assert 2 <= K <= N
a = []
for i in xrange(0, N):
    a.append(input())
a.sort()

minimum = sys.maxint
startindex = 0

for i in xrange(0,N-K+1):
    last = i + K
    tmp = 0
    for j in xrange(i, last):
        for l in xrange(j+1, last):
            tmp += abs(a[j]-a[l])
            if(tmp > minimum):
                break

    if(tmp < minimum):
        minimum = tmp
        startindex = i #end index = startindex + K?

Examples:

N = 7
K = 3
array = [10,100,300,200,1000,20,30]
result = [10,20,30]

N = 10
K = 4
array = [1,2,3,4,10,20,30,40,100,200]
result = [1,2,3,4]