Recent work has shown the importance of considering the adversary’s background knowledge when reasoning about privacy in data publishing. However, it is very difficult
for the d...
Many problems in computer vision can be modeled using
conditional Markov random fields (CRF). Since finding
the maximum a posteriori (MAP) solution in such models
is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
The ability to store and query uncertain information is of great benefit to databases that infer values from a set of observations, including databases of moving objects, sensor r...
The Conditional Restricted Boltzmann Machine (CRBM) is a recently proposed model for time series that has a rich, distributed hidden state and permits simple, exact inference. We ...
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...