ICML Tutorial on Posterior Inference in Big Data

12 May 2014

Max Welling will be co-presenting a tutorial at the International Conference on Machine Learning on Bayesian Posterior Inference in the Big Data Arena. ICML is the leading conference on machine learning.

Abstract: Traditional algorithms for Bayesian posterior inference require processing the entire dataset in each iteration and are quickly getting obsoleted by the data deluge in various application domains. Most successful applications of learning with big data have been with very simple algorithms such as Stochastic Gradient Descent, because they are the only ones that can computationally handle today