Despite the recent proliferation of work on semistructured data models, there has been little work to date on supporting uncertainty in these models. In this paper, we propose a m...
Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently, rese...
Adam Kowalczyk, Alex J. Smola, Peter A. Flach, Tho...
We generalize the unfolding semantics, previously developed for concrete formalisms such as Petri nets and graph grammars, to the setting of (single pushout) rewriting over adhesiv...
Paolo Baldan, Andrea Corradini, Tobias Heindel, Ba...
In the context of automated feeding (orienting) of industrial parts, we study the algorithmic design of traps in the bowl feeder track that filter out all but one orientation of ...
— We consider a collection of robots sharing a common environment, each robot constrained to move on a roadmap in its configuration space. To program optimal collision-free moti...