Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
We describe a very large scale distributed robotic system, involving a team of over 100 robots, that has been successfully deployed in large, unknown indoor environments, over ext...
Internet routing events are known to introduce severe disruption to applications. So far effective diagnosis of routing events has relied on proprietary ISP data feeds, resulting ...
—In practice, one is often faced with incomplete phylogenetic data, such as a collection of partial trees or partial splits. This paper poses the problem of inferring a phylogene...
Daniel H. Huson, Tobias Dezulian, Tobias H. Kl&oum...
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...