Analysis of Distributed Abstract Machines Damien Pous ENS Lyon, France. We illustrate the use of recently developed proof techniques for weak bisimulation sing a generic framework...
Regarding nite state machines as Markov chains facilitates the application of probabilistic methods to very large logic synthesis and formal verication problems. Recently, we ha...
Gary D. Hachtel, Enrico Macii, Abelardo Pardo, Fab...
In this paper we propose an Rprop modification that builds on a mathematical framework for the convergence analysis to equip Rprop with a learning rates adaptation strategy that en...
Aristoklis D. Anastasiadis, George D. Magoulas, Mi...
The problem of learning forest-structured discrete graphical models from i.i.d. samples is considered. An algorithm based on pruning of the Chow-Liu tree through adaptive threshol...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
In this paper we present a method of parameter optimization, relative trust-region learning, where the trust-region method and the relative optimization [21] are jointly exploited...