Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
In many reinforcement learning applications, the set of possible actions can be partitioned by the programmer into subsets of similar actions. This paper presents a technique for ...
The Valued Constraint Satisfaction Problem (VCSP) is a general framework encompassing many optimisation problems. We discuss precisely what it means for a problem to be modelled in...
In distributed systems users need to share sensitive objects with others based on the recipients' ability to satisfy a policy. Attribute-Based Encryption (ABE) is a new parad...
Many important applications exhibit large amounts of data parallelism, and modern computer systems are designed to take advantage of it. While much of the computation in the multi...