Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
We present an iterative approximate solution to the multidimensional assignment problem under general cost functions. The method maintains a feasible solution at every step, and i...
This paper studies the issue of space coordinate change in genetic algorithms, based on two methods: convex quadratic approximations, and principal component analysis. In both met...
Elizabeth F. Wanner, Eduardo G. Carrano, Ricardo H...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
The goal of deconvolution is to recover an image x from its convolution with a known blurring function. This is equivalent to inverting the linear system y = Hx. In this paper we ...