Biological systems are far more complex and robust than systems we can engineer today. One way to increase the complexity and robustness of our engineered systems is to study how ...
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
We will describe three kinds of probabilistic induction problems, and give general solutions for each , with associated convergence theorems that show they tend to give good proba...
Abstract: We introduce the notion of ∧- and ∨-pairs of functions on lattices as an abstraction of the notions of metric and its related entropy for probability distributions. T...
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...