Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
We propose a new method for solving structured CSPs which generalizes and improves the Cyclic-Clustering approach [4]. First, the cutset and the tree-decomposition of the constrai...
High-throughput analytical techniques such as nuclear magnetic resonance, protein kinase phosphorylation, and mass spectroscopic methods generate time dense profiles of metabolites...
Prospero C. Naval, Luis G. Sison, Eduardo R. Mendo...
Recent advances in data processing have enabled the generation of large and complex graphs. Many researchers have developed techniques to investigate informative structures within...
In this work, we study the notion of competing campaigns in a social network. By modeling the spread of influence in the presence of competing campaigns, we provide necessary too...