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

mages

library(mnormt)
mycols <- topo.colors(100,0.5)
xhat <- c(0.2, -0.2)
Sigma <- matrix(c(0.4, 0.3, 
                  0.3, 0.45), ncol=2)
x1 <- seq(-2, 4,length=151)
x2 <- seq(-4, 2,length=151)
f <- function(x1,x2, mean=xhat, varcov=Sigma) 
  dmnorm(cbind(x1,x2), mean,varcov)
z <- outer(x1,x2, f)

nunofernandes-plight

library(mnormt)
mycols <- topo.colors(100,0.5)
xhat <- c(0.2, -0.2)
Sigma <- matrix(c(0.4, 0.3, 
                  0.3, 0.45), ncol=2)
x1 <- seq(-2, 4,length=151)
x2 <- seq(-4, 2,length=151)
f <- function(x1,x2, mean=xhat, varcov=Sigma) 
  dmnorm(cbind(x1,x2), mean,varcov)
z <- outer(x1,x2, f)

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

frozeman

/*
Basically "web3" comes from Mist,
but "Web3" CAN come from  the dapp.

A Dapp has 3 ways to use web3.
2. and 3. would work when in Mist and outside.
*/

// 1. simply use, web3 comes already defined

zerosign

New purely functional data structures published since 1998:

    2001: Ideal Hash Trees, and its 2000 predecessor, Fast And Space Efficient Trie Searches, by Phil Bagwell: Apparently used as a fundamental building block in Clojure's standard library.

    2001: A Simple Implementation Technique for Priority Search Queues, by Ralf Hinze: a really simple and beautiful technique for implementing this important datastructure (useful, say, in the Dijkstra algorithm). The implementation is particularly beautiful and readable due to heavy use of "view patterns".

    2002: Bootstrapping one-sided flexible arrays, by Ralf Hinze: Similar to Okasaki's random-access lists, but they can be tuned to alter the time tradeoff between cons and indexing.

    2003: New catenable and non-catenable deques, by Radu Mihaescu and Robert Tarjan: A new take on some older work (by Kaplan and Tarjan) that Okasaki cites (The most recent version of Kaplan & Tarjan's work was published in 2000). This version is simpler in some ways.

frozeman

// Open the wallet console: Menu -> Develop -> Toggle console ...
// Run the following script

_.each(Wallets.find().fetch(), function(item){
    if(item.address)
        Wallets.update(item._id, {$set: {address: item.address.toLowerCase()}}); 
});
_.each(CustomContracts.find().fetch(), function(item){
    if(item.address)
        CustomContracts.update(item._id, {$set: {address: item.address.toLowerCase()}}); 

nunofernandes-plight

// Open the wallet console: Menu -> Develop -> Toggle console ...
// Run the following script

_.each(Wallets.find().fetch(), function(item){
    if(item.address)
        Wallets.update(item._id, {$set: {address: item.address.toLowerCase()}}); 
});
_.each(CustomContracts.find().fetch(), function(item){
    if(item.address)
        CustomContracts.update(item._id, {$set: {address: item.address.toLowerCase()}}); 

awjuliani

awjuliani