In computer science, the randomized quicksort algorithm has expected runtime O(nlogn). How does linearity of expectation allow us to show this?
# | User | Rating |
---|---|---|
1 | jiangly | 3976 |
2 | tourist | 3815 |
3 | jqdai0815 | 3682 |
4 | ksun48 | 3614 |
5 | orzdevinwang | 3526 |
6 | ecnerwala | 3514 |
7 | Benq | 3482 |
8 | hos.lyric | 3382 |
9 | gamegame | 3374 |
10 | heuristica | 3357 |
# | User | Contrib. |
---|---|---|
1 | cry | 169 |
2 | -is-this-fft- | 165 |
3 | Um_nik | 161 |
3 | atcoder_official | 161 |
5 | djm03178 | 157 |
6 | Dominater069 | 156 |
7 | adamant | 154 |
8 | luogu_official | 152 |
9 | awoo | 151 |
10 | TheScrasse | 147 |
In computer science, the randomized quicksort algorithm has expected runtime O(nlogn). How does linearity of expectation allow us to show this?
Let, x1 < = x2 < = x3....... < = xn
and
p1 + p2 + p3 + ....... + pn = 1
We all know that average of x1, x2, x3......., xn is in [x1,xn] and it is easy to understand.
In a contest, I assumed Expected value = p1 * x1 + p2 * x2 + p3 * x3 + ....... + pn * xn is in [x1,xn] regardless how probability is distributed that means the sum of probability can be 1 in many different ways.
My assumption was right and got ac. I'm interested to know the proof.
TIA
Question 01:
Is there any technique where generating random number within a range is equiprobable ?
Question 02:
What is the extra advantage of the following method 02,03,04 ?
srand(time(NULL);
//Method 01: general approach
int myrand(int mod){
return rand()%mod;
}
//Method 02: Taken form red coder submission.
int myrand(int mod) {
int t = rand() % mod;
t = (1LL*t*RAND_MAX + rand()) % mod;
return t;
}
//Method 03: Taken from red coder submission.
int myrand(int mod) {
return (int) ( (((double) rand() / RAND_MAX) * (mod) ));
}
//Method 04 : Taken from red coder submission.
inline int myrand(int mod) {
return (((long long )rand() << 15) + rand()) % mod;
}
Updated : Idea from diko.
auto seed = chrono::high_resolution_clock::now().time_since_epoch().count();
std::mt19937 mt(seed);
int myrand(int mod) {
return mt()%mod;
}
The problem was set in acm icpc preliminary contest 2017 in Dhaka site. Problem Link : E.Anti Hash
Problem is : you will given a string S of length N consisting of lowercase letters (a-z) only.Also given a base B and mod-value M for doing polynomial hashing. Note : B and M are both prime.
Your task is to find another string T, satisfying all of the following constraints: Length of T is exactly N. T consists of only lowercase letters (a-z). T and S have the same hash value that means, collision happens. For hashing in both case you have to use B and M.
Any idea? Thanks in advance.
If a String is : "Topcoder" and all of it's suffix are :
r,er,der,oder........pcoder,Topcoder
Now consider c++ code:
std::string str = "Topcoder";
const char* pointer = &str[1];
cout<<pointer<<'\n';
Output is: opcoder
What is the complexity of generating of above suffix upto 1 index of length 7? Linear or Constant ?
Is 10^9 computation is possible before 2.00 seconds? If not possible,how my solution works of following problem? Problem link: http://codeforces.me/problemset/problem/851/C Submission: http://codeforces.me/contest/851/submission/30089349
Name |
---|