## Solutions to Exercises in Statistical Learning

I did a bit of spring cleaning and found some solutions to a course using exercises from the book The Elements of …

## C++ Pipeline for Learning Fisher Vectors Using VLFeat

I implemented a C++ pipeline for learning Fisher feature vectors using VLFeat since Matlab should be avoided whenever possible. Also I found …

## Understanding the Metropolis Hasting algorithm – A tutorial

The Problem Say you want to evaluate the expectation of a function over a random variable $$E[f(x)] = \int p(x)f(x)dx$$, or perhaps …

## A short tutorial on Kernel Density Estimation (KDE)

The aim of Kernel Density Estimation(KDE) is: Given a set of $$N$$ samples from a random variable, $$\mathbf{X}$$, possibly multivariate and continuous, …

## Partially fixing numerical underflow for mixture models

In a mixture model the probability of an event $$x$$ is written $$P(x=X) =\sum_{i}\pi_{i}P_{i}(x=X)$$, where $$\pi_{i}$$ is the probability of the …

## On payoff matrices, decision rules, confusion and affinity matrices

Simple post today. Just some definitions and explanations of stuff that is pretty familiar to most people. Payoff / Loss Matrices Payoff …