The key limiting factor in graphical model inference and learning is the complexity of the partition function. We thus ask the question: what are the most general conditions under...
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
A new version of the GRAIL system (Uberbacher and Mural, 1991; Mural et al., 1992; Uberbacher et al., 1993), called GRAILII, has recently been developed (Xu et al., 1994). GRAILII...
Yin Xu, J. Ralph Einstein, Richard J. Mural, Manes...
An understanding of the topological structure of the Internet is needed for quite a number of networking tasks, e.g., making decisions about peering relationships, choice of upstr...
Network edge packet-processing systems, as are commonly implemented on network processor platforms, are increasingly required to support a rich set of services. These multi-servic...
Arun Raghunath, Aaron R. Kunze, Erik J. Johnson, V...