mullr

(ns clj-automated-reasoning.core-match
  (:require [clojure.core.match :as cm]))

(defn simplify1 [e]
  (cm/match [e]
    [(['+ 0 x] :seq)] x
    [(['+ x 0] :seq)] x
    [(['* x 1] :seq)] x
    [(['* 1 x] :seq)] x
    [(['* x 0] :seq)] 0

coatless

#include <RcppArmadillo.h>
#include <omp.h>
using namespace Rcpp;
using namespace arma;

// [[Rcpp::depends(RcppArmadillo)]]
// [[Rcpp::plugins(openmp)]]

// [[Rcpp::export]]
void updateImplicitX_p(arma::mat & X, const arma::mat & Y, const arma::mat & P, const arma::mat & C, double lambda, int cores = 1) {

johnmyleswhite

Papers

Benchmarking seems not to be a main focus of any specific academic field, although the problem has been addressed by many different groups in CS.

Some papers I found interesting:

• http://research.microsoft.com/en-us/um/people/nswamy/papers/bottlenecks-ecoop04.pdf
• http://www.sigmod.org/publications/sigmod-record/0806/p45.dewitt.pdf
• http://daniel-wilkerson.appspot.com/trend-prof.pdf
• http://sape.inf.usi.ch/sites/default/files/publication/EvaluateCollaboratoryTR1.pdf

bitemyapp

The Learning Haskell guide has been moved to a git repo to enable outside contribution

Find it here: https://github.com/bitemyapp/learnhaskell

PhDP

#! /usr/bin/python2

import json

from TwitterAPI import TwitterAPI

c_key = '...'
c_sec = '...'
t_key = '...'
t_sec = '...'

tpoisot

#! /usr/bin/python2

import json

from TwitterAPI import TwitterAPI

c_key = '...'
c_sec = '...'
t_key = '...'
t_sec = '...'

PhDP

open System.Xml.Linq
open FSharp.Data

/// Use F#'s awesome type provider to access arXiv's API.
type StatML = XmlProvider<"http://export.arxiv.org/api/query?search_query=stat.ML&start=0&max_results=1000">

/// Request Stat.ML articles from 'a' to 'b'.
let APIReq (a: int) (b: int) =
    "http://export.arxiv.org/api/query?search_query=stat.ML&start=" + (string a) + "&max_results=" + (string b)

PhDP

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "title": "Scriptoria object",
  "description": "Meta-data about a publication registered in scriptoria",
  "type": "object",
  "properties": {
    "source": {
      "description": "URL of the original repository",
      "type": "string"
    },

tpoisot

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "title": "Scriptoria object",
  "description": "Meta-data about a publication registered in scriptoria",
  "type": "object",
  "properties": {
    "source": {
      "description": "URI of the original repository",
      "type": "string"
    },

PhDP

/**
 * Computes the measure of an English word as defined for the Porter algorithm.
 * The definition of the measure can be found here:
 *    http://snowball.tartarus.org/algorithms/porter/stemmer.html
 *
 * ...but it's overtly complicated. Here's my definition:
 *
 * The *measure* of a word is the number of vowels followed by a consonant.
 *
 * Examples: