vermorel

using System.Reflection;
using System.Reflection.Emit;

public static class DelegateHelper
{
    /// <summary>
    /// Compile the 'Delegate' to a static method.
    /// </summary>
    public static MethodInfo CompileToMethod(Delegate del)
    {

vermorel

using System;
using System.Collections.Generic;
using Xunit;

namespace MyMurmurHash
{
    /// <summary>
    /// Fast hash - non-crypto secure. Intended to detect data storage
    /// corruption.
    /// </summary>

vermorel

// Fast 1D convolution with AXV
// By Joannes Vermorel, Lokad, January 2018
// Released under MIT license

#include <string.h>
#include <stdio.h>
#include <malloc.h> 

/* A simple implementation of a 1D convolution that just iterates over
* scalar values of the input array.

vermorel

using System;
using System.Collections;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using NUnit.Framework;

namespace Lokad
{
    /// <summary>

vermorel

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using NUnit.Framework;

namespace Lokad
{
    /// <summary>
    /// A random forest tailored for regression, treading categorical variables as on ordinals.

vermorel

# A constant 1D tensor that contains an enumeration 0 .. (count - 1).
Range(count) = Splice( array [0..(count-1)] ( i => Constant{i} ) )

# residual units
ResNet(InnerDim, OuterDim, INNODE) = {
  L1 = DenseLayer {InnerDim, activation = ReLU, init = "gaussian"}( INNODE )
  L2 = DenseLayer {OuterDim, activation = Pass, init = "gaussian"}( L1 )
  ResUnit = ReLU(Plus(INNODE, L2))
}.ResUnit

vermorel

using System;
using System.Collections.Generic;
using System.Diagnostics;

namespace Lokad
{
    /// <summary>
    /// Z-Transform is the discrete version of the Laplace transform.
    /// In their transformed form, the convolution of two distributions
    /// is just the point-wise product of their Z-transform coefficients.

vermorel

/// ================ Half.cs ====================
/// The code is free to use for any reason without any restrictions.
/// Ladislav Lang (2009), Joannes Vermorel (2017)

using System;
using System.Diagnostics;
using System.Globalization;

namespace SystemHalf
{

vermorel

using System;
using System.Collections.Generic;
using System.Linq;

namespace Lokad
{
    /// <summary>
    /// Naive Bayesian classifier.
    /// </summary>
    /// <remarks>

vermorel

# Random expansion of monthly data into daily data
# Syntax: convert-daily "c:\LokadData\foo.tsv" 
# Expected columns are Id, Date, Quantity
# By Joannes Vermorel, April 2016

function convert-daily
{
    param
    (
        [string] $file