We propose a novel method for inferring whether X causes Y or vice versa from joint observations of X and Y . The basic idea is to model the observed data using probabilistic late...
Inference of the network structure (e.g., routing topology) and dynamics (e.g., traffic matrices, link performance) is an important component in many network design and management ...
Temporal causal modeling can be used to recover the causal structure among a group of relevant time series variables. Several methods have been developed to explicitly construct te...
Sentence compression holds promise for many applications ranging from summarization to subtitle generation. Our work views sentence compression as an optimization problem and uses...
— This paper develops an approach to the capture and measurement of the information contained in opponents’ bet actions in seven card stud poker. We develop a causal model link...