Learn about the Information Bottleneck Principle (IB).
Francisco Yepes Barrera
Master’s Degree in Chemistry. My professional activity was carried out in the field of software development and scientific computation.. My interests focus on some areas of artificial intelligence, mainly neural networks and genetic algorithms. In the past I worked on hybrid neuroevolutionary systems and their application to industrial problems. I am currently working on a neural network optimization model called “Eigen Artificial Neural Networks” which, starting from an analogy with physical quantum-mechanical systems, uses wave mechanics techniques in their study.
Here's what I've written (so far):
Learn the characteristics of one of the simplest and best-known optimization algorithms: hill climbing.
Learn about important applications of Red-Black trees.
Learn a simple technique for checking errors in the transmission of a binary string
Learn how we can use ping to measure the bandwidth of a network connection.
Learn about the sine-cosine algorithm.
In this tutorial, we’ll study one of the methods used to verify if n is prime without resorting to factorization: the Miller-Rabin method.
Examine computational complexity issues within cryptographic algorithms
Learn how correlation phenomena are generally harmful within a predictive method.
Study weight initialization techniques in artificial neural networks and why they’re important.