Math

Introduction

Recently, I’ve been trying to organize the papers on accelerated reasoning techniques I’ve read over the past year into notes. During this process, I came across Bayesian optimization techniques that utilize Bayes’ theorem, so I decided to write a note to record the essence of Bayes’ theorem.

In simple terms, Bayes’ theorem is a frequently encountered theorem in probability theory that describes the probability of a random event occurring under specific conditions.

Newton’s interpolation is a polynomial interpolation method that constructs a set of polynomial functions using multiple data points. A major advantage is that with the addition of new data, Newton’s interpolation method does not require recalculations from scratch but can instead expand on the existing function.

The probability density function (PDF) is a fundamental concept in probability theory and statistics, describing the probability distribution of a random variable across its range of values.