Stochastic computation is a new alternative approach for iterative computation on factor graphs. In this approach, the information is represented by the statistics of the bit stre...
Saeed Sharifi Tehrani, Shie Mannor, Warren J. Gros...
We present a numerical approximation technique for the analysis of continuous-time Markov chains that describe networks of biochemical reactions and play an important role in the ...
Thomas A. Henzinger, Maria Mateescu, Linar Mikeev,...
Correlation is one of the most widely used similarity measures in machine learning like Euclidean and Mahalanobis distances. However, compared with proposed numerous discriminant ...
In this paper we present an evaluation of selected parallel strategies for Simulated Annealing and Simulated Evolution, identifying the impact of various issues on the effectivene...
Sadiq M. Sait, Syed Sanaullah, Ali Mustafa Zaidi, ...
In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...