The hurdles in solving Constrained Optimization Problems (COP) arise from the challenge of searching a huge variable space in order to locate feasible points with acceptable solut...
Abu S. S. M. Barkat Ullah, Ruhul A. Sarker, David ...
The problem of optimal node density maximizing the Neyman-Pearson detection error exponent subject to a constraint on average (per node) energy consumption is analyzed. The spatial...
Recent work has shown how information theory extends conventional full-rationality game theory to allow bounded rational agents. The associated mathematical framework can be used ...
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms correspo...
We introduce a new approach to constrained Independent Component Analysis (ICA) by formulating the original, unconstrained ICA problem as well as the constraints in mutual informa...