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...
In this paper we present an integrated view for modeling and reasoning for context applications using OWL DL. In our case study, we describe a task driven approach to model typica...
Anni-Yasmin Turhan, Thomas Springer, Michael Berge...
This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how p...
Terry Koo, Amir Globerson, Xavier Carreras, Michae...
This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
Managing long verification error traces is one of the key challenges of automated debugging engines. Today, debuggers rely on the iterative logic array to model sequential behavior...