The aim of this paper is to show that machine learning techniques can be used to derive a classifying function for human brain signal data measured by magnetoencephalography (MEG)...
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Garbage collectors are notoriously hard to verify, due to their lowlevel interaction with the underlying system and the general difficulty in reasoning about reachability in graph...
Contracts are behavioural descriptions of Web services. We devise a theory of contracts that formalises the compatibility of a client to a service, and the safe replacement of a s...
We establish several approximate max-integral-flow / minmulticut theorems. While in general this ratio can be very large, we prove strong approximation ratios in the case where th...