pyk

Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod
tempor incididunt ut labore et dolore magna aliqua.

pyk

package main

import (
	"fmt"
	"log"
	"os"
)

func main() {
	file, err := os.OpenFile("output.txt", os.O_RDWR, os.ModePerm)

pyk

pyk

* {
    font-size: 12pt;
    font-family: monospace;
    font-weight: normal;
    font-style: normal;
    text-decoration: none;
    color: black;
    cursor: default;
}

pyk

1. General Background and Overview

• Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
• Models and Issues in Data Stream Systems
• Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

pyk

#include <stdio.h>

int
main()
{
    /* character */
    char a;
    a = 's';
    printf("char a\t= %c\n", a);

pyk

This is bunch of vim tips that I gather from the internet.

Project-specific configuration

" forces vim to source .vimrc file if it present in working directory
set exrc
" restrict usage of some commands in non-default .vimrc files
set secure

Navigate source code

pyk

#include <stdio.h>

long long fib(long long n);
long long fibs[100];

long long
main()
{
    long long i;

pyk

#include <stdio.h>
#include <math.h>

int
main()
{
    int n;

    for(n = 1; n < 10000; n++) {
        if((8*pow(n,2)) < (64*n*log(n))) {

pyk

/* compile: gcc -o insertion-sort insertion-sort.c */
#include <stdio.h>

int
main()
{
    int i;
    int A[6] = {5, 2, 4, 6, 1, 3};

    for(i = 1; i < 6; i++) {