In this paper we show how to train statistical machine translation systems on reallife tasks using only non-parallel monolingual data from two languages. We present a modificatio...
The objective of this work is to create a framework for the optimization of embedded software. We present algorithms and a tool flow to reduce the computational effort of programs,...
Eui-Young Chung, Luca Benini, Giovanni De Micheli,...
Models of neurons based on iterative maps allows the simulation of big networks of coupled neurons without loss of biophysical properties such as spiking, bursting or tonic bursti...
Carlos Aguirre, Doris Campos, Pedro Pascual, Eduar...
Performance evaluation of computer networks through traditional packet-level simulation is becoming increasingly difficult as networks grow in size along different dimensions. Due...
Daniel R. Figueiredo, Benyuan Liu, Yang Guo, James...
Abstract-- This paper considers uncertain constrained systems, and develops a method for computing a probabilistic output admissible (POA) set which is a set of initial states prob...
Retrieving music from large digital databases is a demanding computational task. The cost for indexing and searching depends not only on the computational effort of measuring music...
Data-driven haptic rendering requires processing of raw recorded signals, which leads to high computational effort for large datasets. To achieve real-time performance, one possib...
Koza has shown how automatically defined functions (ADFs) can reduce computational effort in the GP paradigm. In Koza's ADF, as well as in standard GP, an improvement in a par...
— The E∗ algorithm is a path planning method capable of dynamic replanning and user-configurable path cost interpolation. It calculates a navigation function as a sampling of ...