mccormick.northwestern.edu

COMP_SCI 474: Probabilistic Graphical Models

Probabilistic graphical models are a powerful technique for handling uncertainty in machine learning. The course will cover how probability distributions can be represented in graphical models, how ...
JSTOR Daily

A BAYESIAN GRAPHICAL MODELING APPROACH TO MICRORNA REGULATORY NETWORK INFERENCE

It has been estimated that about 30% of the genes in the human genome are regulated by microRNAs (miRNAs). These are short RNA sequences that can down-regulate the levels of mRNAs or proteins in ...
Concordia University

Advances in probabilistic sentential decision diagram learning and inference

Probabilistic Sentential Decision Diagrams (PSDDs) are an elegant framework for learning from and reasoning about data. They provide tractable representations of discrete probability distributions ...
JSTOR Daily

LATENT VARIABLE GRAPHICAL MODEL SELECTION VIA CONVEX OPTIMIZATION

Suppose we observe samples of a subset of a collection of random variables. No additional information is provided about the number of latent variables, nor of the relationship between the latent and ...