debasishg

General Background and Overview

1. 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.
2. Models and Issues in Data Stream Systems
3. 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
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

cjyar

package memoize

import (
	"fmt"
	"reflect"
)

// fptr is a pointer to a function variable which will receive a
// memoized wrapper around function impl. Impl must have 1 or more
// arguments, all of which must be usable as map keys; and it must

icholy

package main

import (
	"unicode/utf8"
)

type Item string
type Stream chan Item
type Acc string

jellybeansoup

#!/bin/sh

##
# Install autoconf, automake and libtool smoothly on Mac OS X.
# Newer versions of these libraries are available and may work better on OS X
#
# This script is originally from http://jsdelfino.blogspot.com.au/2012/08/autoconf-and-automake-on-mac-os-x.html
#

export build=~/devtools # or wherever you'd like to build