The Hierarchical Dirichlet Process Hidden Semi-Markov Model

In my work at DARPA, I’ve been exposed to hidden Markov models in applications as diverse as temporal pattern recognition such as speech, handwriting, gesture recognition, musical score following, and bioinformatics. My background is in stochastic modeling and optimization, and hidden Markov models are a fascinating intersection between my background Continue Reading

Gradient Descent

It has been awhile since I’ve studied optimization, but gradient descent is always good to brush up on. Most optimization involves derivatives. Often known as the method of steepest descent, gradient descent works by taking steps proportional to the negative of the gradient of the function at the current point. Continue Reading