The theory of Markov set-chains is applied to derive upper and lower bounds on the capacity of finite-state channels that are tighter than the classic bounds by Gallager. The new ...
We consider semi-supervised classification when part of the available data is unlabeled. These unlabeled data can be useful for the classification problem when we make an assumpti...
Robust Bayesian inference is the calculation of posterior probability bounds given perturbations in a probabilistic model. This paper focuses on perturbations that can be expresse...
We prove that perfect distributions exist when using a finite number of bits to represent the parameters of a Bayesian network. In addition, we provide an upper bound on the prob...
With a graph G = (V, E) we associate a collection of non-negative real weights vV {i,v : 1 i m} uvE{ij,uv : 1 i j m}. We consider the probability distribution on {f : V {1,...