We examine the problem of transmitting in minimum time a given amount of data between a source and a destination in a network with finite channel capacities and non–zero propaga...
Dimitrios Kagaris, Spyros Tragoudas, Grammati E. P...
Background: In sequence analysis the multiple alignment builds the fundament of all proceeding analyses. Errors in an alignment could strongly influence all succeeding analyses an...
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
Abstract--Reconstruction algorithms for fluorescence tomography have to address two crucial issues : (i) the ill-posedness of the reconstruction problem, (ii) the large scale of nu...
We consider scheduling real-time distributable threads in the presence of node/link failures and message losses in large-scale network systems. We present a distributed scheduling...