In recent years, extraction of temporal relations for events that express sentiments has drawn great attention of the Natural Language Processing (NLP) research communities. In thi...
We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
Sriraam Natarajan, Prasad Tadepalli, Eric Altendor...
Abstract—This work considers the problem of reaching consensus in an unreliable linear consensus network. A solution to this problem is relevant for several tasks in multi-agent ...
Fabio Pasqualetti, Antonio Bicchi, Francesco Bullo
Researchers have defined a number of process modeling methods and have developed in-roads to process-centered environments that support process modeling and project control. Howev...
Stephanie White, Susan Fife Dorchak, John T. Keane...