Overview
Explore the foundations of generative models in this 33-minute video lecture on Boltzmann Machines. Delve into the core concepts of these early generative models, including their goal of learning probability distributions of data through stochastic rules and latent representations. Examine the Boltzmann Distribution, stochastic update rules, and the Contrastive Hebbian Rule. Investigate the role of hidden units and the development of Restricted Boltzmann Machines. Gain insights into the historical significance and practical applications of these models in machine learning and artificial intelligence.
Syllabus
Introduction
Goal of Boltzmann Machines
Boltzmann Distribution
Stochastic Update Rule
Contrastive Hebbian Rule
Hidden Units
Restricted Boltzmann Machines
Conclusion & Outro
Taught by
Artem Kirsanov