In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Abstract. The theory of bulk-synchronous parallel computing has produced a large number of attractive algorithms, which are provably optimal in some sense, but typically require th...
Mohammad R. Nikseresht, David A. Hutchinson, Anil ...
Abstract. We deal with two intimately related subjects: quasi-randomness and regular partitions. The purpose of the concept of quasi-randomness is to measure how much a given graph...
Abstract. We provide a new characterization of certain zero-knowledge protocols as non-interactive instance-dependent commitment-schemes (NIC). To obtain this result we consider th...
How do design decisions impact the quality of the resulting software? In an empirical study of 52 ECLIPSE plug-ins, we found that the software design as well as past failure histo...