This work was motivated by a discussion that two of the coauthors (computer science professors) had with the other coauthor (a law professor and a former computer crime Trial Atto...
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Knowledge processing is very demanding on computer architectures. Knowledge processing generates subcomputation paths at an exponential rate. It is memory intensive and has high c...
Huge amounts of social multimedia is being created daily by a combination of globally distributed disparate sensors, including human-sensors (e.g. tweets) and video cameras. Taken...