We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
This paper investigates the application of causal inference methodology for observational studies to software fault localization based on test outcomes and profiles. This methodo...
We address the problem of incorporating user preference in automatic image enhancement. Unlike generic tools for automatically enhancing images, we seek to develop methods that ca...
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
Britton Wolfe, Michael R. James, Satinder P. Singh
An important issue arising from Peer-to-Peer applications is how to accurately and efficiently retrieve a set of K best matching data objects from different sources while minimizi...