We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
In this paper, we address the problem of preserving generated data in a sensor network in case of node failures. We focus on the type of node failures that have explicit spatial s...
We pose the question: how do we efficiently evaluate a join operator, distributed over a heterogeneous network? Our objective here is to optimize the delay of output tuples. We di...
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
Interactive network-based navigation over large urban environments raises difficult problems due to the size and complexity of these scenes. In this paper, we present a clientser...