hdu-5734 Acperience(数学)
题目链接:
Acperience
Time Limit: 4000/2000 MS (Java/Others)
Memory Limit: 65536/65536 K (Java/Others)
Convolutional neural networks show reliable results on object recognition and detection that are useful in real world applications. Concurrent to the recent progress in recognition, interesting advancements have been happening in virtual reality (VR by Oculus), augmented reality (AR by HoloLens), and smart wearable devices. Putting these two pieces together, we argue that it is the right time to equip smart portable devices with the power of state-of-the-art recognition systems. However, CNN-based recognition systems need large amounts of memory and computational power. While they perform well on expensive, GPU-based machines, they are often unsuitable for smaller devices like cell phones and embedded electronics.
In order to simplify the networks, Professor Zhang tries to introduce simple, efficient, and accurate approximations to CNNs by binarizing the weights. Professor Zhang needs your help.
More specifically, you are given a weighted vector W=(w1,w2,...,wn). Professor Zhang would like to find a binary vector B=(b1,b2,...,bn) (bi∈{+1,−1}) and a scaling factor α≥0 in such a manner that ∥W−αB∥2 is minimum.
Note that ∥⋅∥ denotes the Euclidean norm (i.e. ∥X∥=x21+⋯+x2n−−−−−−−−−−−√, where X=(x1,x2,...,xn)).
The first line contains an integers n (1≤n≤100000) -- the length of the vector. The next line contains n integers: w1,w2,...,wn (−10000≤wi≤10000).
#include <iostream>
#include <cstdio>
#include <cstring>
#include <algorithm>
#include <cmath>
#include <bits/stdc++.h>
#include <stack> using namespace std; #define For(i,j,n) for(int i=j;i<=n;i++)
#define mst(ss,b) memset(ss,b,sizeof(ss)); typedef long long LL; template<class T> void read(T&num) {
char CH; bool F=false;
for(CH=getchar();CH<'0'||CH>'9';F= CH=='-',CH=getchar());
for(num=0;CH>='0'&&CH<='9';num=num*10+CH-'0',CH=getchar());
F && (num=-num);
}
int stk[70], tp;
template<class T> inline void print(T p) {
if(!p) { puts("0"); return; }
while(p) stk[++ tp] = p%10, p/=10;
while(tp) putchar(stk[tp--] + '0');
putchar('\n');
} const LL mod=1e9+7;
const double PI=acos(-1.0);
const int inf=1e9;
const int N=1e5+10;
const int maxn=500+10;
const double eps=1e-6; int a[N],n;
LL sum=0,ans=0;
LL gcd(LL x,LL y)
{
if(y==0)return x;
return gcd(y,x%y);
}
int main()
{
int t;
read(t);
while(t--)
{
read(n);
sum=0,ans=0;
For(i,1,n)
{
read(a[i]);
sum=sum+(LL)a[i]*a[i];
if(a[i]<0)ans=ans-a[i];
else ans=ans+a[i];
}
LL x=(LL)n;
LL g=gcd(x*sum-ans*ans,x);
cout<<(x*sum-ans*ans)/g<<"/"<<x/g<<endl; }
return 0;
}
hdu-5734 Acperience(数学)的更多相关文章
- HDU 5734 Acperience(数学推导)
Problem Description Deep neural networks (DNN) have shown significant improvements in several applic ...
- HDU 5734 Acperience ( 数学公式推导、一元二次方程 )
题目链接 题意 : 给出 n 维向量 W.要你构造一个 n 维向量 B = ( b1.b2.b3 ..... ) ( bi ∈ { +1, -1 } ) .然后求出对于一个常数 α > 0 使得 ...
- HDU 5734 Acperience(返虚入浑)
p.MsoNormal { margin: 0pt; margin-bottom: .0001pt; text-align: justify; font-family: Calibri; font-s ...
- HDU 5734 Acperience (推导)
Acperience 题目链接: http://acm.hdu.edu.cn/showproblem.php?pid=5734 Description Deep neural networks (DN ...
- hdu 5734 Acperience 水题
Acperience 题目连接: http://acm.hdu.edu.cn/showproblem.php?pid=5734 Description Deep neural networks (DN ...
- HDU 5734 Acperience
Acperience Time Limit: 4000/2000 MS (Java/Others) Memory Limit: 65536/65536 K (Java/Others)Total ...
- hdu 5734 Acperience(2016多校第二场)
Acperience Time Limit: 4000/2000 MS (Java/Others) Memory Limit: 65536/65536 K (Java/Others)Total ...
- HDU 5734 Acperience (公式推导) 2016杭电多校联合第二场
题目:传送门. #include <iostream> #include <algorithm> #include <cstdio> #include <cs ...
- HDU 5734 A - Acperience
http://acm.hdu.edu.cn/showproblem.php?pid=5734 Problem Description Deep neural networks (DNN) have s ...
- Acperience HDU - 5734
Deep neural networks (DNN) have shown significant improvements in several application domains includ ...
随机推荐
- Engine中如何截取线上指定两点间的线段?
//调用 IPolyline newLine = GetSubCurve(polyline, p1, p2); ESRI.ArcGIS.Display.IScreenDisplay screenD ...
- iOS -- MBProgressHUB
高级: http://www.jianshu.com/p/485b8d75ccd4 //只有小菊花 - (void)indeterminateExample { // Show the HUD on ...
- win7 32位安装pyqt
参考 http://blog.csdn.net/fairyeye/article/details/6607981 http://www.cnblogs.com/toSeek/p/6363036.htm ...
- TCP通过滑动窗口和拥塞窗口实现限流,能抵御ddos攻击吗
tcp可以通过滑动窗口和拥塞算法实现流量控制,限制上行和下行的流量,但是却不能抵御ddos攻击. 限流只是限制访问流量的大小,是无法区分正常流量和异常攻击流量的. 限流可以控制本软件或者应用的流量大小 ...
- linux下命令行的查找顺序
由下可知,linux通过$PATH的路径顺序,由左至由依次查找某个程序,如果有两个路径下都有这个程序,以先找到的为准 [rpc_server]$ which 23/usr/bin/which: no ...
- Samp免流软件以及地铁跑酷的自校验分析
[文章标题]:Samp免流软件以及地铁跑酷的自校验分析 [文章作者]: Ericky [作者博客]: http://blog.csdn.net/hk9259 [下载地址]: 自行百度 [保护方式]: ...
- NMM3DViewer 设计
在FrameworkInterfaces工程的INMM3DServer.cs中定义了 岩石材料结构 BlockMaterial -----> StrBLOCKProperty publ ...
- HDMI各版本对比
转:一文看懂从HDMI1.0到HDMI2.1的历代规格变化 hdmi HDMI详解 https://blog.csdn.net/xubin341719/article/details/7713450 ...
- AndroidManifest具体解释之Application(有图更好懂)
可以包括的标签: <activity> <activity-alias> <service> <receiver> <provider> & ...
- 官方Caffe-windows 配置与示例运行
http://blog.csdn.net/guoyk1990/article/details/52909864 标签: caffewindows配置训练自己的数据 2016-10-24 13:34 1 ...