For many supervised learning problems, we possess prior knowledge about which features yield similar information about the target variable. In predicting the topic of a document, ...
Ted Sandler, John Blitzer, Partha Pratim Talukdar,...
Users of topic modeling methods often have knowledge about the composition of words that should have high or low probability in various topics. We incorporate such domain knowledg...
When constructing a Bayesian network, it can be advantageous to employ structural learning algorithms to combine knowledge captured in databases with prior information provided by...
We present a new variational level-set-based segmentation
formulation that uses both shape and intensity prior information
learned from a training set. By applying Bayes’
rule...
We introduce an algorithm that guides the user to tag
faces in the best possible order during a face recognition assisted
tagging scenario. In particular, we extend the active
l...
Ashish Kapoor, Gang Hua, Amir Akbarzadeh and Simon...