—The 0/1 loss is an important cost function for perceptrons. Nevertheless it cannot be easily minimized by most existing perceptron learning algorithms. In this paper, we propose...
Abstract. This paper presents a fast algorithm for robust registration of shapes implicitly represented by signed distance functions(SDF). The proposed algorithm aims to recover th...
Muayed S. Al-Huseiny, Sasan Mahmoodi, Mark S. Nixo...
Iterative distributed algorithms are studied for computing arithmetic averages over networks of agents connected through memoryless broadcast erasure channels. These algorithms do...
Ruggero Carli, Giacomo Como, Paolo Frasca, Federic...
We describe two techniques for fast multiple-precision evaluation of linearly convergent series, including power series and Ramanujan series. The computation time for N bits is O(...
We discuss the integration of the expectation-maximization (EM) algorithm for maximum likelihood learning of Bayesian networks with belief propagation algorithms for approximate i...