In this paper we present an alternative approach to interprocedurally g linear inequality relations. We propose an abstraction of the effects of procedures through convex sets of t...
We present a new machine learning approach to the inverse parametric sequence alignment problem: given as training examples a set of correct pairwise global alignments, find the p...
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
This paper describes a new variational method for estimating disparity from stereo images. The stereo matching problem is formulated as a convex programming problem in which an ob...
— Cellular simultaneous recurrent neural network has been suggested to be a function approximator more powerful than the MLP’s, in particular for solving approximate dynamic pr...