Sequential Minimal Optimization (SMO) is currently the most popular algorithm to solve large quadratic programs for Support Vector Machine (SVM) training. For many variants of this...
We design polynomial time approximation schemes (PTASs) for Metric BISECTION, i.e. dividing a given finite metric space into two halves so as to minimize or maximize the sum of di...
Wenceslas Fernandez de la Vega, Marek Karpinski, C...
In this paper we solve the general problem of designing a feedback controller to reach a set of facets of an n-dimensional simplex in finite time, for a system evolving with linea...
We discover significant value-dependent programming energy variations in multi-level cell (MLC) flash memories, and introduce an energy-aware data compression method that minimize...
In this paper we initiate the study of discrete random variables over domains. Our work is inspired by work of Daniele Varacca, who devised indexed valuations as models of probabi...