Belief Propagation Algorithms with Applications to Cancer Genomics
Presidential Lectures are free public colloquia centered on four main themes: Biology, Physics, Mathematics and Computer Science, and Neuroscience and Autism Science. These curated, high-level scientific talks feature leading scientists and mathematicians and are intended to foster discourse and drive discovery among the broader NYC-area research community. We invite those interested in the topic to join us for this weekly lecture series.
Belief propagation is an algorithmic method that provides solutions to many complex machine-learning problems.
Belief propagation algorithms have numerous applications in coding theory, vision and many other areas of machine learning. In this talk, Christian Borgs will give an introduction to belief propagation, discuss how the accuracy of belief propagation has been rigorously established, and present recent applications to systems biology. Examples include simple applications to yeast networks, complex applications in the discovery of pathways in cancer genomics, and modifications to distinguish patient-specific pathways from more general disease pathways.