Awareness of the need for robustness in distributed systems increases as distributed systems become an integral part of day-to-day systems. Tolerating Byzantine faults and possessi...
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
The structural comparison of proteins has become increasingly important as a means to identify protein motifs and fold families. In this paper we present a new algorithm for the c...
Many algorithms for processing probabilistic networks are dependent on the topological properties of the problem's structure. Such algorithmse.g., clustering, conditioning ar...
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....