Abstract. A well studied and difficult class of scheduling problems concerns parallel machines and precedence constraints. In order to model more realistic situations, we consider ...
Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
In this paper, we study several linear-time equivalences (Markovian trace equivalence, failure and ready trace equivalence) for continuous-time Markov chains that refer to the pro...
Verena Wolf, Christel Baier, Mila E. Majster-Ceder...
Abstract. The aim of this paper is to show how the P systems with replicated rewriting can be modeled by X-machines (also called Eilenberg machines). In the first approach, the par...
Joaquin Aguado, Tudor Balanescu, Anthony J. Cowlin...
Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
Ioannis Psorakis, Theodoros Damoulas, Mark A. Giro...