A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
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...
We develop an integrated probabilistic model to combine protein physical interactions, genetic interactions, highly correlated gene expression network, protein complex data, and d...
Episodic knowledge is often stored in the form of textual narratives written in natural language. However, a large repository of such narratives will contain both repetitive and n...
Accurate estimation of quality of online services is both an important and difficult problem, since a service has many interdependent quality attributes influenced by several co...