— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
The paper studies the problem of distributed static parameter (vector) estimation in sensor networks with nonlinear observation models and imperfect inter-sensor communication. We...
A central problem in bioinformatics and systems biology is the selection of appropriate models in a rational and systematic way. This fundamentally combinatorial problem can be re...
Eric Yang, Timothy Maguire, Martin L. Yarmush, Ioa...
A distributed system is commonly modelled by a graph where nodes represent processors and there is an edge between two processors if and only if they can communicate directly. In ...
We present a noisy-OR Bayesian network model for simulation-based training, and an efficient search-based algorithm for automatic synthesis of plausible training scenarios from co...
Eugene Grois, William H. Hsu, Mikhail Voloshin, Da...